Computer-Assisted Drug Design 9780841205215, 9780841206779, 0-8412-0521-3

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Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.fw001

Computer-Assisted Drug Design

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.fw001

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Computer-Assisted Drug Design Edward C. Olson,

EDITOR

The Upjohn Company

Ralph E . Christoffersen,

EDITOR

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.fw001

University of Kansas

Based on a symposium sponsored by the Divisions of Computers in Chemistry and Medicinal Chemistry at the ACS/CSJ Chemical Congress, Honolulu, Hawaii, April 2-6, 1979.

ACS SYMPOSIUM SERIES

112

AMERICAN CHEMICAL SOCIETY WASHINGTON, D. C. 1979

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Library of CongressCIPData

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.fw001

Symposium on Computer-Assisted Drug Design, Honolulu, 1979. Computer-assisted drug design. (ACS symposium series; 112 ISSN 0097-6156) "Based on a symposium sponsored by the Division of Computers in Chemistry [and the Medicinal Chemistry Division] at the ACS/CSJ Chemical Congress, Honolulu, Hawaii, April 2-6, 1979." Includes bibliographies and index. 1. Chemistry, Pharmaceutical—Data processing— Congresses. 2. Structure-activity relationship (Pharmacology)—Data processing—Congresses. I. Olson, Edward C. II. Christoffersen, Ralph E., 1937. III. American Chemical Society. Division of Computers in Chemistry. IV. American Chemical Society. Division of Medicinal Chemistry. V. ACS/CSJ Chemical Congress, Honolulu, 1979- VI. Title. VII. Series: American Chemical Society. ACS symposium series; 112. RS401.S95 1979 ISBN 0-8412-0521-3

615'.191'02854 79-21038 ASCMC8 112 1-619 1979

Copyright © 1979 American Chemical Society All Rights Reserved. The appearance of the code at the bottom of the first page of each article in this volume indicates the copyright owner's consent that reprographic copies of the article may be made for personal or internal use or for the personal or internal use of specific clients. This consent is given on the condition, however, that the copier pay the stated per copy fee through the Copyright Clearance Center, Inc. for copying beyond that permitted by Sections 107 or 108 of the U.S. Copyright Law. This consent does not extend to copying or transmission by any means—graphic or electronic—for any other purpose, such as for general distribution, for advertising or promotional purposes, for creating new collective works, for resale, or for information storage and retrieval systems. The citation of trade names and/or names of manufacturers in this publication is not to be construed as an endorsement or as approval by ACS of the commercial products or services referenced herein; nor should the mere reference herein to any drawing, specification, chemical process, or other data be regarded as a license or as a conveyance of any right or permission, to the holder, reader, or any other person or corporation, to manufacture, reproduce, use, or sell any patented invention or copyrighted work that may in any way be related thereto. PRINTED IN THEUNITEDSTATESOFAMERICA

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.fw001

ACS Symposium Series M. Joan Comstock, Series Editor

Advisory Board Kenneth B. Bischoff

James P. Lodge

Donald G. Crosby

John L. Margrave

Robert E. Feeney

Leon Petrakis

Jeremiah P. Freeman

F. Sherwood Rowland

E. Desmond Goddard

Alan C. Sartorelli

Jack Halpern

Raymond B. Seymour

Robert A. Hofstader

Aaron Wold

James D. Idol, Jr.

Gunter Zweig

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.fw001

FOREWORD The ACS SYMPOSIUM SERIES was founded in 1974 to provide a medium for publishing symposia quickly in book form. The format of the Series parallels that of the continuing ADVANCES IN CHEMISTRY SERIES except that in order to save time the papers are not typeset but are reproduced as they are submitted by the authors in camera-ready form. Papers are reviewed under the supervision of the Editors with the assistance of the Series Advisory Board and are selected to maintain the integrity of the symposia; however, verbatim reproductions of previously published papers are not accepted. Both reviews and reports of research are acceptable since symposia may embrace both types of presentation.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

PREFACE 'he existence of structure—activity relationships was recognized as early as 1868 by Crum-Brown and Frazer at Edinburgh University, and this postulate led, quite naturally, to attempts to modify (design) structures via chemical procedures to demonstrate increased biological activity. For many years this type of drug design proceeded empirically through the "chemical intuition" of organic and medicinal chemists. As the empirical data base was created, relationships were observed and methods for quantitating these correlations were developed.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.pr001

A

The advent of the "age of computers" has made possible the computation of many indices not previously accessible and the use of sophisticated correlation methods to discover correlations among these indices in multivariable systems. The diverseness of the methods that are currently available and their application is indicated by the far ranging content of this symposium on Computer-Assisted Drug Design. The goal of the symposium was to bring together experts in many of the specific disciplines that have been applied to drug design, to explore the interaction between these areas, and to examine the role of the computer in the overall process of drug design. The major areas treated by participants include receptor modeling, organic syntheses, quantitative structure-activity relations, quantum mechanics, pattern recognition, and molecular mechanics. It is obviously not possible to cover in depth such a diverse array of topics in a single symposium. Therefore, it was the intent to establish the current state of the art in each of the previously mentioned fields and to show the necessity for the application of all methods in any integrated program of drug design. There can be no doubt that the art or science (as the case may be) of drug design is still in its infancy, and that significant improvements in all technologies are essential to permit progress toward the goal of designing therapeutic agents for specific maladies. However, the potential rewards for success are enormous, both from a practical and fundamental point of view, which increases the urgency of such efforts. Indeed, efforts to sharpen the tools of both "lead-finding" and "leadoptimization" techniques and to apply them early-on in the development xi In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

of novel or improved therapeutic agents may well be essential for the continued development of new drugs as the costs of drug development escalate far more rapidly than the general inflationary increase. The Upjohn Company Kalamazoo, MI 49001

EDWARD C . OLSON

University of Kansas Lawrence, KS 66045 June 8, 1979. Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.pr001

RALPH E. CHRISTOFFERSEN

xii In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Quantum Pharmacology: Recent Progress and Current Status

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch001

RALPH E . CHRISTOFFERSEN Chemistry Department, University of Kansas, Lawrence, KS 66045

As even a casual perusal of the current literature will indicate, the development of theoretical techniques and application to problems in biology in general and drug design in particular has expanded substantially in recent years. This has been due in part to the appearance of techniques and computing equipment that allow examination of large molecular systems, but has also been motivated substantially by the potential practical use of these techniques in the design of new medicinal agents. When combined with similar advances in experimental biochemistry and pharmacology, the beginnings of a new field can be identified, in which problems of interest to pharmacology can be examined at the molecular level. It is the status of these efforts that are of interest in the current symposium. More particularly, in this opening review we shall focus primarily upon the use of theoretical techniques to study problems in pharmacology. In order to produce a study of manageable size, this review will include only those studies involved with drug design per se, i.e., theoretical studies of isolated drug molecules, solvated drug molecules, or model drug-receptor interactions of potential use in the design of new medicinal agents. It will therefore omit a large number of important studies on other biological problems such as photosynthesis, the structure and function of nucleic acids, polypeptides and proteins, and many others. However, as will become apparent below, the activity in the area of "theoretical drug design" itself has been high, with significant progress occurring in several aspects. Literature Review Since the work in this area has been reviewed previously (1, 2) for the period up through the end of 1975, only studies published during 1976-1978 will be included here. In this period, 0-8412-0521-3/79/47-112-003$05.00/0 © 1979 American Chemical Society

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch001

4

COMPUTER-ASSISTED DRUG DESIGN

80 s t u d i e s o f i n t e r e s t t o t h i s review appeared and were found i n 13 d i f f e r e n t j o u r n a l s and books. Combined with the 130 a r t i c l e s p r i o r t o 1974 (_L) and the 24 s t u d i e s reported i n 1975 ( 2 ) , i t i s seen that over 230 s t u d i e s have now appeared i n t h i s area. The t h e o r e t i c a l techniques used f o r the s t u d i e s i n t h i s review i n c l u d e ab i n i t i o techniques (3-6_), semi-empirical techniques such as PCILO ( 7 ) , CNDO and TNDO (£, 9_), IEHT (10-12_), MINDO (13), and HMO (14), e m p i r i c a l p o t e n t i a l s (15-17), and other techniques (18-21). In a d d i t i o n , s e v e r a l review a r t i c l e s and books i n t h i s area have appeared (22-24) during t h i s p e r i o d . The 80 s t u d i e s themselves (25-104) are summarized i n Table 1, where they have been categorized~~by both the k i n d o f agents that were s t u d i e d and the methodology used. Before d i s c u s s i n g these f u r t h e r , i t i s important t o note s e v e r a l t h i n g s . F i r s t , the assignment o f a study t o a p a r t i c u l a r type o f agent f r e q u e n t l y cannot be done unambiguously due t o the f a c t that drugs f r e q u e n t l y have more than one k i n d o f a c t i v i t y . Thus, the e n t r i e s i n Table 1 may have a p p l i c a b i l i t y i n more than simply the category i n which they have been l i s t e d . A l s o , i n some cases s e v e r a l d i f f e r ent t h e o r e t i c a l techniques have been employed, i n which case a given study may have more than one entry i n Table 1. Next, i t i s important t o remember that the a c t i o n o f a drug i s determined i n general by a v a r i e t y o f f a c t o r s , i n c l u d i n g : 1. Absorption. 2. Excretion. 3. Catabolism, 4. Binding t o Plasma P r o t e i n . 5. Penetration o f the Blood-Brain B a r r i e r . 6. A f f i n i t y f o r the Receptor. 7. Intrinsic Activity. Each o f these f a c t o r s needs t o be considered i f a d e t a i l e d understanding o f drug a c t i o n i s t o be obtained. However, the theor e t i c a l s t u d i e s described i n t h i s review w i l l d e a l t y p i c a l l y with only one o r two o f the f a c t o r s described above (e.g. , receptor a f f i n i t y and/or i n t r i n s i c a c t i v i t y ) , and w i l l be o f d i r e c t a i d i n drug design only i f the other f a c t o r s have a r e l a t i v e l y constant c o n t r i b u t i o n i n the s e r i e s o f drugs s t u d i e d . Turning t o the s p e c i f i c s t u d i e s reported during 1976-78, there are s e v e r a l general comments o f i n t e r e s t . Of greatest importance among these i s the demonstrable change i n the sophist i c a t i o n o f the techniques used i n t h e o r e t i c a l s t u d i e s . For example, only 8% o f the s t u d i e s reported p r i o r t o 1975 (1) used ab i n i t i o quantum mechanical techniques , while over 25% o f the s t u d i e s reported i n the 1975-78 p e r i o d used ab i n i t i o techniques. While the use o f ab i n i t i o techniques does not per se i n d i c a t e an improvement i n the accuracy o f the r e s u l t s (due t o l i m i t e d b a s i s sets and other l i m i t a t i o n s ) , i t does i n d i c a t e that a " s t a t e - o f - t h e - a r t " that was p r e v i o u s l y thought t o be obtainable f o r " s m a l l " o r "medium-sized" chemical systems i s now a v a i l a b l e f o r use on the s u b s t a n t i a l l y l a r g e r systems o f t y p i c a l i n t e r e s t

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

1.

CHRISTOFFERSEN

5

Quantum Pharmacology

Table 1. T h e o r e t i c a l Studies on Systems o f Pharmacological I n t e r e s t . Method Used Agent

IEHT

CNDO/2

INDO

PCILO

Ab I n i t i o

Other

A. Agents A f f e c t i n g Nerve Function

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch001

1. Adrenergics 2. A n a l g e s i c s

46

68 104 80

35,66

80

30,40 34,36 , 62 ,76 . 74,75, 80,94 99 96,98

28,38 87 61,63, 78,98, 100

3. A n a l e p t i c s 84

27,31

8. Anticonvulsants and Muscle Relaxants

48

53

9. Antidepressants and Stimulants

32

4. Anaesthetics 5. A n t i - a n g i n a l Agents 6. A n t i - a n x i e t y Agents 7. Anti-arrhythmic Agents

10. A n t i p a r k i n s o n i a n Agents 11. A n t i p s y c h o t i c s 12. A n t i t u s s i v e s 13. C h o l i n e r g i c s and Anticholinergics

37

44

56

39

14. Emetics and Anti-emetics 15. Hallucinogens

97,70

J6. Hypnotics and Depressants

69

25,43, 64,71, 73,77, 85

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

79,97

COMPUTER-ASSISTED DRUG DESIGN

6

Table 1.

(cont.)

Agent

IEHT

CNDO/2

INDO

PCILO

Ab I n i t i o

Other

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch001

B. Agents A f f e c t i n g Cardiovas c u l a r Function 1. V a s o d i l a t o r s and Vasoconstrictors

42,102

2. Hypotensive and Hypertensive Agents

45

3. Antihyperchol e s t e r o l Agents 4. Ant i coagulant s 5. Cardiac Glycosides 6. Vasopressor Agents

C. Agents A f f e c t i n g Endocrine Function 1. S t e r o i d Hormones 2. Prostaglandins 88,95

3. P o l y p e p t i d e , P r o t e i n , and Other Hormones 4. Thyroid Agents 5. Hypoglycaemic Agents

49

D. A n t i - i n f e c t i v e and Chemotherap e u t i c Agents 1. Anti-amoebic Agents 2. A n t i b i o t i c s

58

51, 101

92

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

54,60, 65 ,93

1.

CHRISTOFFERSEN

Table 1.

7

(cont.)

Agent 3.

Quantum Pharmacology

IEHT

Anticancer Agents

CNDO/2

INDO

PCILO

52,57, 67,89, 90,91

Ab I n i t i o

Other

55,81, 83,90

41,86

4. A n t i f u n g a l Agents 50

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch001

5. A n t i m a l a r i a l Agents 6. Antimycobact e r i a l Agents 7. A n t i p a r a s i t i c s 8.

Antiprotozoan Agents

9. A n t i s e p t i c s 10. A n t i v i r a l s

E.

33 59 82

Miscellaneous

1. A n t i h i s t a m i n i c and A n t i a l l e r genic Agents and Histamine

26,29, 72

2. Carbohvdrat e s

103

3. Vitamins 4. I n s e c t i c i d e s and Insect Hormones 5. Antiinflammat o r y Agents

47

6. A n t i s e c r e t o r y Agents a.

b.

References are l i s t e d c h r o n o l o g i c a l l y by year. Chronological o r d e r i n g w i t h i n a given year was not attempted. While i t was intended t h a t a l l r e l e v a n t references i n the p e r i o d 1976-1978 should be i n c l u d e d i n t h i s t a b l e , there are undoubtedly many inadvertant omissions f o r which the author apologizes i n advance. A d d i t i o n a l references from t h i s p e r i o d are welcomed. E n t r i e s i n the t a b l e r e f e r t o the reference that describes the study that was c a r r i e d out.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch001

8

Figure 1.

Morphine structure and atom numbering

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch001

1.

Quantum Pharmacology

CHRISTOFFERSEN

9

i n drug design. The techniques have evolved i n s e v e r a l other ways as w e l l . For example, e l e c t r o s t a t i c p o t e n t i a l maps have been found to be a q u i t e u s e f u l and s e n s i t i v e t o o l (Z5, 26_, 41, 44_, 46_, 57_, 71, 7_5, 99_) f o r i d e n t i f y i n g r e a c t i v i t y c h a r a c t e r i s t i c s of drugs, at l e a s t i n e l e c t r o p h i l i c r e a c t i o n s . Since these maps can be c a l c u l a t e d d i r e c t l y from the wavefunction, and are more s e n s i t i v e measures of the e l e c t r o n i c charge d i s t r i b u t i o n f o r chemical r e a c t i o n s than, e.g., the net charges and bond orders from a p o p u l a t i o n a n a l y s i s , t h e i r i n t r o d u c t i o n and use represent an important development i n the kinds o f t h e o r e t i c a l t o o l s a v a i l a b l e f o r use. In a d d i t i o n , the use o f s t a t i s t i c a l mechanics i n the i n t e r p r e t a t i o n o f conformational energies has f i n a l l y begun t o be considered (2S_ 79). A l s o , the use of pseudopotential theory, at l e a s t f o r cases when second-row atoms are i n v o l v e d , has been t r i e d i n s e v e r a l cases (43, 64, 83, 100), and shows good potential. Not only has the methodology developed s i g n i f i c a n t l y , but the models used t o represent b i o l o g i c a l events have improved s u b s t a n t i a l l y i n many cases. For example, not only have i s o l a t e d molecules been s t u d i e d , but models of the drug-receptor complex have been developed i n s e v e r a l cases (37_, 43_, 52, 56, 71, 77_, 81, 89, 90.5 97). In other cases, models f o r the t r a n s i t i o n s t a t e i t s e l f have been i n v e s t i g a t e d (6j0). In a d d i t i o n , solvent and other environmental e f f e c t s are i n c l u d e d more commonly than before (28_, 3J8, 39_, 40_, 49_ 5_5_, 79), even though i t i s recognized t h a t a f u l l y s a t i s f a c t o r y model o f solvent e f f e c t s that i s computationally f e a s i b l e i s not yet a v a i l a b l e . On the other hand, there are a v a r i e t y of. areas where subs t a n t i a l developmental e f f o r t s i n methodology and/or b i o l o g i c a l models are needed. Perhaps most s t r i k i n g i s the need f o r i n c l u s i o n of s u b s t a n t i a l l y l a r g e r numbers of geometric degrees of freedom when studying conformational c h a r a c t e r i s t i c s of molecules. While the study of the e n e r g e t i c dependence of one or two d i h e d r a l angle v a r i a t i o n s i s perhaps u s e f u l as a s t a r t i n g p o i n t , i t i s c l e a r that such s t u d i e s are l i m i t e d i n the conc l u s i o n s that can be e x t r a c t e d from them, and may i n some cases lead to incorrect conclusions. For example, even i n the case of " r i g i d " o p i a t e s , i t i s c l e a r that the f l e x i b i l i t y present i n the s t r a i n e d , m u l t i - r i n g s t r u c t u r e i s s i g n i f i c a n t and cannot be ignored. Even the C 1 2 - C 1 3 bond i n morphine (see Figure 1 ) , which forms the nexus of each of the f i v e r i n g s , can be shown t o allow a 30° v a r i a t i o n w i t h i n 3 kcal/mole or l e s s , using e i t h e r experimental or c a l c u l a t e d r e s u l t s (7^_). T h i s i s an important f l e x i b i l i t y t h a t should not be ignored f o r s e v e r a l reasons. F i r s t , changes i n t h i s angle w i l l change s u b s t a n t i a l l y the d i s t a n c e from the quaternary n i t r o g e n to the aromatic moiety (Ring A i n Figure 1 ) , which i s a f e a t u r e that i s thought by many to be important i n o p i a t e r e c e p t o r i n t e r a c t i o n s . Next, i f comparisons to other o p i a t e s 9

9

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

10

are made and the molecular f l e x i b i l i t i e s of morphine and the comparison molecule are i g n o r e d , i t i s p o s s i b l e t o conclude that no s t r u c t u r a l s i m i l a r i t y e x i s t s when i n f a c t such s i m i l a r i t i e s do e x i s t . For example, when only two d i h e d r a l angle variations were c o n s i d e r e d ^ , 106), i t was concluded that meperidine and morphine could not be matched from a geometric p o i n t of view. On the other hand, i f a l l bond d i s t a n c e s , bond angles and dihed r a l angles are allowed t o r e l a x (74), a good f i t of the two molecules can be achieved at only modest e n e r g e t i c cost (-3.6 kcal/mole f o r the a x i a l form of meperidine, and 6.9 k c a l / mole f o r the e q u a t o r i a l form of meperidine). In a r e l a t e d i s s u e , the development of r e l i a b l e , f a s t , and g e n e r a l l y a p p l i c a b l e e m p i r i c a l p o t e n t i a l s (or other procedures) that w i l l allow examination o f l a r g e numbers of degrees o f freedom i n a wide v a r i e t y of c l a s s e s o f organic compounds remains an important unsolved problem. Just as i n the case o f neglect of geometric degrees o f freedom, the use of naive approximations or p o t e n t i a l f u n c t i o n s that omit obvious terms of importance cannot be expected t o provide r e l i a b l e r e s u l t s (78). More g e n e r a l l y , while there have been s u b s t a n t i a l c o n t r i b u t i o n s t o the development of e m p i r i c a l p o t e n t i a l s f o r s p e c i a l i z e d kinds of molecules, e.g., polypeptides (107), corresponding p o t e n t i a l s f o r the broad range of molecules that are t y p i c a l l y encountered i n drug design are not c u r r e n t l y a v a i l a b l e .

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0 5

New

Directions

In a d d i t i o n t o the developments already r e f e r r e d t o above, there are s e v e r a l other new d i r e c t i o n s that can be i d e n t i f i e d i n the recent l i t e r a t u r e , that i n d i c a t e the kinds o f a d d i t i o n a l advances that can be expected i n the next s e v e r a l years. As a f i r s t example i n t h i s r e g a r d , i t i s o f i n t e r e s t t o consider a study r e p o r t e d by E. Clementi and c o l l a b o r a t o r s (108) i n 1978. In t h i s paper, the manner of t r e a t i n g enzymic r e a c t i o n s using t h e o r e t i c a l techniques was g e n e r a l i z e d s u b s t a n t i a l l y from e a r l i e r work. Since the d e s c r i p t i o n of enzyme-substrate i n t e r a c t i o n s encounters the same kinds of d i f f i c u l t i e s as the desc r i p t i o n of drug-receptor i n t e r a c t i o n s , t h i s study may provide a good i n d i c a t i o n o f new d i r e c t i o n s and c a p a b i l i t i e s that can be expected t o develop f u r t h e r i n the near f u t u r e . In t h i s approach, enzymic r e a c t i o n s are considered t o be d i v i s i b l e i n t o two separate but r e l a t e d steps c a l l e d "macrodeformations" and "mierodeformations. Macrodeformations are intended to i n c l u d e the s t r u c t u r a l a l t e r a t i o n s that a f f e c t the e n t i r e enzyme p l u s s u b s t r a t e during the approach and r e a c t i o n of the substrate and departure o f the products. On the other hand, microdeformations recognize t h a t , a f t e r the o v e r a l l enzymesubstrate s t r u c t u r e i s approximately determined a f t e r approach of the s u b s t r a t e , a d e t a i l e d d e s c r i p t i o n of the chemical r e a c t i o n needs t o be considered. These c o n s i d e r a t i o n s assume that the ,f

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch001

1.

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r e a c t i o n i s a r e l a t i v e l y " l o c a l i z e d " event, and that only a r e l a t i v e l y small number of moieties i n and around the a c t i v e s i t e plus the substrate need to be considered. Of course, the two processes cannot be r i g o r o u s l y separated as d e s c r i b e d , and a sequence of macrodeformations plus microdeformations i s used to model the various steps along the r e a c t i o n path. For the d e s c r i p t i o n o f the two kinds of processes, d i f f e r e n t kinds of t h e o r e t i c a l techniques were used. For macrodeformations, the primary processes that are assumed t o be o c c u r r i n g are a l a r g e number of non-bonded i n t e r a c t i o n s that l e a d to the i n t r o d u c t i o n of the substrate i n t o the a c t i v e s i t e (or departure of the products). For such processes, e m p i r i c a l p o t e n t i a l s are appropriate t o use f o r s e v e r a l reasons. First, e v a l u a t i o n of the t o t a l energy can be done r a p i d l y enough so that a l a r g e number of atoms and degrees of freedom can be examined. Next, as long as no bonds are made or broken, i t i s p o s s i b l e f o r e m p i r i c a l p o t e n t i a l s to provide a s a t i s f a c t o r y t h e o r e t i c a l framework. In the case of microdeformations, the a c t u a l chemical react i o n at the a c t i v e s i t e i s considered, and a d e t a i l e d ab i n i t i o quantum mechanical formulation i s used. For the i n i t i a l s t u d i e s described i n 1978, a minimum b a s i s set SCF c a l c u l a t i o n was c a r r i e d out, but the concept i s q u i t e general. As a f i r s t example, the c y s t e i n e p r o t e i n a s e , papain, was studied i n i t s c a t a l y t i c cleavage of peptide s u b s t r a t e s . The enzyme contains over 200 r e s i d u e s , and the p a r t i c u l a r mechanism that has been proposed by Drenth, et a l (109) was chosen f o r examination. In the macrodeformation steps, no l e s s than 73 residues plus substrate were considered, s t a r t i n g e s s e n t i a l l y from papain coordinates from X-ray s t u d i e s . In the main, the r e s u l t s of macrodeformation s t u d i e s o f substrate entry are s t r u c t u r e s that are r e l a x e d e n e r g e t i c a l l y from the X-ray c r y s t a l coordinates, i n c l u d i n g the formation of s e v e r a l new hydrogen bonds and the movement of s e v e r a l atoms i n the a c t i v e s i t e i n a manner that w i l l f a c i l i t a t e the subsequent enzyme-substrate r e a c t i o n . In the mierodeformation s t u d i e s , low energy s t r u c t u r e s f o r various intermediates were sought, i n c l u d i n g the form of the a t t a c k i n g species and the s t r u c t u r e of the t e t r a h e d r a l intermediate. It i s not expected that e i t h e r the s t r u c t u r e "refinements" of the enzyme or substrate that occurred during macrodeformation steps or the e n e r g e t i c or s t r u c t u r a l features found as a r e s u l t of mierodeformation steps are r e l i a b l e enough at t h i s stage t o provide conclusive new i n s i g h t i n t o the enzymatic behavior of papain. However, these s t u d i e s i n d i c a t e c l e a r l y that the " s t a t e o f - t h e - a r t " has now changed s u b s t a n t i a l l y , and that meaningful models of enzyme-substrate or drug-receptor i n t e r a c t i o n s can now be examined using t h e o r e t i c a l techniques. Another example that i l l u s t r a t e s new d i r e c t i o n s of i n t e r e s t r e l a t e s t o the experimental c h a r a c t e r i z a t i o n at the molecular

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l e v e l o f drug-receptor complexes. S p e c i f i c a l l y , the X-ray s t u d i e s of S o b e l l and c o l l a b o r a t o r s (110-11?) on the b i n d i n g o f drugs t o DNA models provide a good example o f the l e v e l o f d e t a i l i n d e s c r i b i n g drug-receptor i n t e r a c t i o n s t h a t i s now p o s s i b l e experimentally . The p a r t i c u l a r system t h a t was s t u d i e d i n v o l v e d the b i n d i n g of ethidium, a known DNA i n t e r c a l a t o r , t o two d i f f e r e n t model DNA s t r u c t u r e s [ 5 - i o d o u r i d y l y l ( 3 - 5 ) a d e n o s i n e and 5 - i o d o c y t i d y l y l ( 3 - 5 ) guanosine], followed by c r y s t a l l i z a t i o n of the complexes and a c q u i s i t i o n p l u s a n a l y s i s o f s u f f i c i e n t X-ray data t o allow atomic r e s o l u t i o n ( i . e . , standard d e v i a t i o n s of +0.1A f o r bond lengths and ±5° f o r bond a n g l e s ) . The DNA-drug models used embody a l a r g e number o f the f e a t u r e s known t o be important, i . e . , double stranded DNA " m i n i - h e l i x e s " are formed, with ethidium i n t e r c a l a t e d between two p a i r s o f hydrogen bonded bases that are connected by the u s u a l sugar-phosphate backbone. These s t u d i e s give r i s e t o a v a r i e t y o f important s t r u c t u r a l f e a t u r e s o f such complexes, as w e l l as t o provide s e v e r a l mechanistic hypotheses t h a t can be i n v e s t i g a t e d f u r t h e r u s i n g t h e o r e t i c a l techniques. For example, these s t u d i e s suggest t h a t drug i n t e r c a l a t i o n r e s u l t s i n a h e l i c a l screw d i s l o c a t i o n i n the DNA double h e l i x , whose magnitude determines the r e l a t i v e r i n g overlap between an i n t e r c a l a t e d drug molecule and adjacent base p a i r s . A l s o , conformational changes i n the sugar-phosphate backbone accompany drug i n t e r c a l a t i o n , which l e d t o the suggestion that DNA " k i n k s " f i r s t , followed by i n t e r c a l a t i o n o f the drug. Such observations and suggestions, while very important c o n t r i b u t i o n s , a l s o r a i s e a s e r i e s o f questions which need f u r t h e r study, and f o r which t h e o r e t i c a l techniques are now a v a i l a b l e . Thus, both t h e o r e t i c a l and experimental s t u d i e s i n d i c a t e t h a t s i g n i f i c a n t new d i r e c t i o n s can be expected i n the next s e v e r a l years t h a t w i l l enhance s u b s t a n t i a l l y the a b i l i t y t o c a r r y out drug design u s i n g techniques h e r e t o f o r e not a v a i l a b l e . Furthermore, c u r r e n t and l i k e l y developments i n both hardware and software f o r minicomputers w i l l extend even f u r t h e r the o p p o r t u n i t i e s f o r use o f s o p h i s t i c a t e d t h e o r e t i c a l techniques on problems i n drug design. !

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Acknowledgement s The author would l i k e t o express h i s deep a p p r e c i a t i o n t o the Upjohn Company f o r t h e i r c o n t i n u i n g support o f t h i s r e s e a r c h , and t o Drs. E.C. Olson, B.V. Cheney, D. Duchamp and many others at the Upjohn Company f o r t h e i r e x c e l l e n t comments and c o l l a b o r a t i o n over many years. In a d d i t i o n , support f o r t h i s symposium and t o t h i s author from the H a r r i s Corporation i s g r a t e f u l l y acknowledged.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch001

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Tsai, C., Jain, S.C. and Sobell, H.M., J. Mol. Biol., (1977), 114, 301-315.

111.

Jain, S.C., Tsai, C. and Sobell, H.M., J. Mol. Biol., (1977), 114, 317-331.

112.

Sobell, H.M., Tsai, C., Jain, S.C. and Gilbert, S.G., J. Mol. Biol., (1977), 114, 333-365.

RECEIVED

June

8, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

2 Parameters and Methods in Quantitative StructureActivity Relationships ROMAN OSMAN, H A R E L WEINSTEIN, and JACK PETER GREEN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

Department of Pharmacology, Mount Sinai School of Medicine of The City University of New York, New York, NY 10029

In studies of quantitative structure activity relationships (QSAR), the relative potencies of a series of drugs are subjected to analysis with the hope that biological potency will be described by a mathematical equation. QSAR is an actuarial or statistical method in which only objective data are used with no intrusion of models or mechanistic hypotheses. The equation that is obtained not only accounts for the relative potencies of the compounds, but from it are deduced predictions of the potencies of untested compounds; if the equation is valid, the predictions are ineluctable. The method thus has the capacity of yielding new (structurally related) drugs with desired potency, perhaps drugs with enhanced selectivity or fewer side effects. Further, in the method that is most widely used, the equation contains a parameter(s) that reflects a property related to the structural characteristics of the molecules. Therefore, the equation has often been assumed to provide insight into mechanisms that determine the action of drugs. In fact, the parameters that account for the biological potency are usually not truly empirical, observed entities, but rather abstractions. These parameters are frequently reified, burdened with a concrete meaning they were not designed to bear, and in this process the true molecular mechanisms may become obfuscated. Further, to infer a mechanism from a correlation is to assume that the correlation implies a causal relationship between the dependent and independent variables, when in fact the two may be conjoint but not causally related. Causality can be inferred only if a testable mechanistic hypothesis is offered that relates the correlation parameters to the observed biological activity. The attempt to correlate biological activity with chemical structure in quantitative terms assumes that a functional dependence exists between the observed biological response and certain physicochemical properties of molecules. Without a mechanistic model one obtains it by an empirical correlation. A rational way to define such empirical relationships is within the extrathermodynamic approach (1). Although extrathermodynamic relationships 0-8412-0521-3/79/47-112-021$13.55/0 © 1979 American Chemical Society In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

22

COMPUTER-ASSISTED DRUG DESIGN

do not directly follow from the axioms of thermodynamics, they are s t i l l able to express, i n a simple way, relations among free energies and other thermodynamic properties. Furthermore, extrathermodynamic relationships also implicitly contain the relation between microscopic properties (e.g., electronic densities, atomic structure, etc.) and macroscopic properties (e.g., free energies). Hence, extrathermodynamic relationships can be used to relate observable properties to structure.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

A.

The extrathermodynamic derivation of QSAR parameters

We derive the extrathermodynamic relationships as a basis for the definition and understanding of the parameters for QSAR. This derivation i s similar to that of Grunwald and L e f f l e r (1). The theoretical derivation of extrathermodynamical relationships i s based on the arbitrary division of a molecule into regions, usually two: the basic structure R, and the substituent X (1, 2). An additivity postulate then enables one to express the p a r t i a l free energy of the substance (or other related property) as a sum of independent contributions, each representing the arb i t r a r i l y defined parts, and an interaction term between the two parts (equation 1). F, 'RX " R F

+

F

+

X

(1)

X

R,X

The additivity postulate i s acceptable when the change i n the property of the basic structure R upon substitution with X i s r e l atively small (i.e., small perturbations). The subject of interest i n relating reactivity (or biological activity) to structure i s the change i n the property of the compound upon interaction with a system, chemical or biological. The change i n the property i s the difference between i t s f i n a l and i n i t i a l value. Applying the additivity approximation results i n equation 2. * -

?

P

RX " RX +

1

^x'-^x )

+

(2

>

Since the substituent i s located at some distance from the reactive center we can assume that the change i n i t s contribution, X - F *, w i l l be negligible. This leaves equation 3.

F

x

R,X')

(3)

In the unsubstituted compound the change i s

(4)

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

2.

23

Structure-Activity Relationships

OSMAN ET AL.

The effect of the substituent on this reaction or interaction i s therefore 6

AF

AF

R RX "

AF

RX " RH (I

"

(I

X

( 5 )

R,X " *R,X> ~ R,H - R,H>

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

which consists only of the interaction terms. At this stage i t i s impossible to express the effect of the substituent independently of the reaction. To overcome this deficiency one applies a separability postulate (equation 6) which assumes that the interaction terms are factorable. X

R,X

•

h '

6

*x

It i s this interaction between R and X (i.e., I „) that mediates the effects of X on the reactivity of RX. Using'the separability R

X during the reaction i s negligibly small, we rewrite equation 5 6

R *RX A

-

< R X

"

F

^

^

X

-

(

V

7

)

Equation 7 clearly shows that the separation of the effect of the substituent on the reaction has been achieved i n terms of a substituent constant, I - I , and a parameter related to the reaction, I - I *. x

R

1.

fl

R

Substituent constants for electronic and steric effects.

The well known Hammett parameters (3, 18) are obtained d i rectly from equation 7 by a r b i t r a r i l y setting I„ to zero, and defining p - I - 1 ^ . Identifying S R A F ^ with log f x (where ^ f

R

K

H and K are the dissociation constants of X-substituted and unsubstituted benzoic acids, respectively) we obtain the Hammett equation (3, 4) *x log 7T- = pa (8) *H where a i s the substituent constant and p i s the reaction constant. The effect of a given substituent i n different reactions w i l l be expressed by different p values. The additivity and separability postulates have two interesting corollaries. The additivity postulate permits us to extend equation 1 to cases where many substituents exist on R. As an example, for the substituents X and Y, H

F

RXY

-

F

R

+

F

X

+

F

Y

+

I

R , X

+

I

E J

+

I

M

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

(

9

)

COMPUTER-ASSISTED DRUG DESIGN

24

If the interaction between the substituents I y i s small, equation 7 can be written as * x

6

A?

R RXY

=

~ ^ ^ X "

+

V

(I

10

Y - V )

< >

Again setting 1^ to zero we may write the Hammett equation as K

XY

log

P (o" + CJ )

-

x

UD

Y

or i n general form

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

*XY

log g - " = pla (12) The additive nature of the substituent constants i s expressed i n equation 12, which states that the influence of several substituents i s equal to the sum of the individual effects of each substituent alone. The additivity rule i s usually reasonably well obeyed without any significant deviations (2, 5, 6, 7, 8). The substituents may have different effects i n different molecules or when i n different positions on the same molecule and are hence called constitutive. The constitutive nature of a i s reflected for example i n the different values for o * (i.e., a ) and c r (i.e., a ) for the same substituent. The separability postulate implicitly assumes that there i s a single interaction mechanism ( I ) between R and X , described by equation 6. This may not be true. For example, the Hammett equation i s limited to only para and meta substituents, because an ortho substituent would add a steric interactions to the I term. Many examples in which the simple Hammett equation does'not hold because the assumption of a single interaction i s not valid are known, and w i l l be discussed below. The second corollary i s useful when equation 6 cannot describe I . Invoking additivity of interaction terms equation 6 becomes meta

p a r a

m

p

Rx

Rx

Rx

9

X

R,X

1R * * X + R * X

"

J

J

+

H I

S

H E R

O

R

D

E

R

interactions

(13)

where J and J describe additional interaction variables between R and X . Following the derivation i n equations 2-7 and neglecting higher order interactions, we can write R

5

x

A

R *RX

* •

< R " h^hi (>i°i + p a X

~ V

f

2

2

+

(J

R

f

J

- R

i ) ( J

J

X " H> (14)

This treatment can be generalized to many interactions. In equation 14 the different a's represent substituent constants that are believed to be related to independent properties of the system and the different p's indicate that different r e a c t i v i t i e s (e.g.,

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

2.

25

Structure-Activity Relationships

OSMAN ET AL.

polar and steric) are associated with these properties (see below). In principle, extrathermodynamic relationships that deviate from the simple Hammett equation (equation 8) can be treated by equation 14. The major problem i s the determination of the d i f ferent sets of a s , (e.g., 0*1 set and 0*2 set) i n a way that w i l l indeed reflect their relation to independent properties. An example of such a procedure i s the separation of polar and steric effects (10). The need for such a separation arose when a nearly complete lack of correlation was observed between substituent effects represented by the Hammet a constants and the rates for a l kaline hydrolysis of aliphatic systems (12). Inspection of the structures indicated that the proximity of the substituents to the reaction site was a common feature. The steric interaction between R and X had to be considered separately from the electronic effects. Polar substituent constants were thus defined as the difference between the rate constants of base and acid catalyzed hydrolysis of esters. From the structural similarity of the transition states for these reactions (equation 15) i t was assumed that the difference i n their charge reflects only the polar effect of the substituent 0 OH Ho0 I 1 R-C-OR (15) R— C-OR^ acidic 1 OR^" hasic OH

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

f

+

1

v

The polar substituent constant, 0*, i s therefore defined (11, 12) as a*

2.48

{log o B

1 1__ 2.48 4T

(log*B X

log) o A

k

-

K

log^B)

(16)

X a

where B and A refer to base and acid catalyzed hydrolysis, k represents rate constants of hydrolysis of substituted acetates, and k the rate constants of the unsubstituted acetate ester which serves as a reference. The factor 2.48 was a r b i t r a r i l y introduced so that o* and a have the same range of numerical values. The rea c t i v i t y related to the polar substituent constants can be expressed as i n equation 17, Q

log(*L_) o

= p*a*

(17)

k

The observation that polar effects i n acid hydrolysis are much less important than the steric effects prompted introduction of the steric substituent constants, E (13, 14). g

(18)

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

26

COMPUTER-ASSISTED DRUG DESIGN

where A and k have the same meaning as i n equation 16. With the definition of a* and E , rate constants of reactions in which pol a r and steric effects were operative could be correlated by equation 19. Q

g

log(]$_) o

=

p*cr* + sE

(19)

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

k

This example i l l u s t r a t e s the p o s s i b i l i t y of separating a multitude of interaction mechanisms into apparently independent terms each of which i s meant to reflect distinct properties of the system. The importance of such a separation i s not only i n i t s a b i l i t y to correlate observed properties with substituent constants but i n any mechanistic implications i t may possess. Further ident i f i c a t i o n of the relation between measured properties (e.g., rate or equilibrium constant) and distinct molecular properties (e.g., electronic densities, molecular structure, etc.) provides a basis for formulating the mechanism of the reaction. The v a l i d i t y of this separation i s determined by the s t a t i s t i c a l v a l i d i t y of equation 19 and by the v a l i d i t y of the assumption that substituent constants (e.g., a* and E ) represent single and independent Interaction mechanisms between the substituent, X, and the molecule, R, (e.g., polar and steric effects). The v a l i d i t y of equation 19 i n empirically correlating the observed rate constants with the polar and steric parameters i s determined by the independence of the parameters. It can be shown that o* does not correlate with E to any significant degree. Regression of a* on E (10) gives the following equation g

g

g

a*

=

(-0.2±0.2)E + (0.3±0.2)

(20)

g

n=25, r=0.04, s=0.801 It i s clear that a* and E are indeed almost orthogonal. The assumption that a substituent constant represents a single interaction mechanism i s supported by the large number of structure-activity relationships described by equation 8 (4, 17). However, the same linear relationship can also hold for cases i n which several interaction mechanisms are important i f their r e l a tive contributions remain constant (1). Some of the risks i n identifying a substituent constant with a single interaction mechanism become clear i n examining the relation between o and o . If only a single interaction mechanism i s represented by a i t follows (1) that the difference, o -a , should be a constant. Table I (compiled from data i n (1)) shows that i t i s not. g

p

m

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

m

2.

OSMAN ET AL.

27

Structure-Activity Relationships

Table I. Dependence of o^-Gp on the substituent. Substituent NH C(CH ) CH 2

3

3

3

OCH OH OC H F CI COCH3 Br CN N0 3

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

6

5

2

Hence, the assumption of a single Interaction mechanism i s not valid* Hammett (18) recognized this discrepancy and attributed i t to inductive and resonance effects (4). It was argued that o represents the inductive effect and the difference (o -a ) the resonance (i.e., mesomeric effect) (19, 20, 21). Further improvements i n the separation into inductive and mesomeric effects are discussed below. m

p

2.

m

Parameters representing the effect of the medium

Early i n this century, Meyer (109) and Overton (110) showed that the relative potencies of drugs that affect the nervous system correlated with their oil/water partition coefficients. F i f t y years later i t was shown that partition coefficients i n different solvent systems were correlated (111), thus establishing the basis for an extrathermodynamical treatment of partition coefficients. As a result a new substituent constant, IT, emerged (23, 24). For a substituent X, i r i s defined as x

logP

x

- logP

H

(21)

where P and P are the partition coefficients of the substituted and unsubstituted molecules, respectively, i n the octanol/water system. Since the properties (i.e., partition coefficients) from which TT i s obtained are related to the different solvation of tin molecules i n different solvents (i.e., octanol and water), we can analyze the substituent constant by an extrathermodynamic treatment of substituent and solvent effects. We define the terms on the right side of equation 21 from the respective equations 22 and 23. x

R

x

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

28

COMPUTER-ASSISTED DRUG DESIGN

(RX)O

W ; X F

^

(RH) ^

(RH)

0

;

W

P

=

Within the extrathermodynamic approximation, the p a r t i a l free energy of a molecule i n a solvent (e.g., i n water, W) can be written as F

W

W

+

-

(F

X>W

+

WR,X>W

(

2

7

)

Here we use the usual assumption of additivity of terms, representing the parts of the molecule, R and X, and the interaction between them, I j ^ . We now introduce the f i r s t assumption about the effect of the solvent: i t can be represented as an interaction term for i t s effect on each of the terms i n equation 27. F

= R

F

= X

W W

< R.X>W I

F

+ I

F

+ I

-

28

R,W

< >

X,W

(29)

VX+YX.W

(

3

0

)

The terms ^ and I ^ represent respectively the solvation of the R part and the X part of the molecule by the solvent, i . e . , water. The term J ^ represents the effect of solvation on the interaction between'R'and X. Since this i s a second order term, we can assume that i t i s small compared to f i r s t order terms and neglect i t for the time being. We define this as the f i r s t x

x R

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

2.

29

Structure-Activity Relationships

OSMAN ET AL.

approximation (1). Applying equations 27 and 30 with the appropriate subscripts for the substituent and the solvent and taking into account the f i r s t approximation, we can write equation 26 as AF = ( ( F ) X

-

W

(F ) )-((F ) X

0

H

W

-

(F ) ) (( R,X>W H

0

+

I

" ( ^ R . ^ W " ^ R . ^ o ) " < X,W " I ,0> X

X

" < R,X>o) I

) J

J

(

4

1

)

Thus, for the TT constants for the same molecular system RX depends linearly on the solvent systems i n which they were determined. Since TT i s an additive-constitutive property of the molecule we can obtain logP from the TT values of the constituting parts (23, 24). The linear relation between logP values for the same compound i n different solvents should also hold. This i s r e f l e c ted i n the linear relation between partition coefficients i n d i f ferent solvent systems as expressed by Collander (111) logP

83 2

alogP + b 1

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

(42)

COMPUTER-ASSISTED DRUG DESIGN

32

Thus, Collander's equation 42, which was established from empirical studies (111), i s theoretically derived from the extrathermodynamic treatment of solvent effects and i s obtained as a result of the second approximation which takes into account the effects of solvation on the interaction term between R and X, J Q. If we now regard the interaction of drugs (in water) with tne'biophase as a partitioning phenomenon, equation 42 becomes the basis for the use of the partition coefficient i n octanol/water, P-p as a model for the partition coefficient between biophase and water, p . R

x

2

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

B.

The empirical framework for definition of QSAR parameters*

Numerical values for the structural parameters of QSAR are obtained from an evaluation of the effect of the substituent on the properties (e.g., the rate or equilibrium constants) of a model reaction. The c l a s s i f i c a t i o n of these parameters i s therefore model dependent. The model reactions are chosen to represent the most pervasive types of physicochemical phenomena (e.g., dissociation reactions, hydrolysis, substitution reactions, partition between solvents). 1.

The c l a s s i f i c a t i o n of o constants

The derivation of a values from the model reaction used by Hammett (18) assumes that the substituted benzoic acids dissolve in water and do not undergo side reactions. Furthermore, when a strong interaction occurs between the substituent and the benzene ring, the basic assumption of the extrathermodynamic relationships i s violated. This may result i n large a values which do not obey the Hammett equation. One example i s the presence of a strongly electron withdrawing or electron donating group in the para position. In order to overcome this problem a different model reaction i s chosen. Taft (43, 44) suggested the use of benzoic acids in which the substituent was isolated from the ring by a CH2 group to determine a new scale denoted a°, which to a large extent overlaps with the a scale. The major drawback of this method i s that the p for this reaction i s small, thus increasing the error i n a°. To overcome this problem the hydrolysis of substituted phenylacet i c esters was proposed as a model reaction because i n this series the reactivity i s more sensitive to substitution (45, 46, 47). The advantage i n this new scale of a° i s i t s uniformity and i t s unbiased treatment of substituents. Its shortcoming i s that the scale i s assumed to be free from a model error; the only error i s in the experimental measurement of the dissociation constants. To minimize the error i t was suggested (4) that a should be defined as a parameter that best f i t s the whole body of data from different model reactions. This can be obtained by iterative methods. For lack of appropriate s t a t i s t i c a l and computative methods, this approach was not used u n t i l recently (48, 50). In

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

2.

Structure-Activity Relationships

OSMAN ET AL.

33

this work (48, 50) the model was defined i n analogy to the Hammett equation as logK

±k

=

*

k

+ p c k

±

+ e

(43)

± k

The subscripts i^ refer to substituents and k to reactions (the models). The parameter coincides with logKQ , i . e . , the rate or equilibrium constant for the unsubstituted compound, and e^ contains both the experimental and model errors. In the s t a t i s t i c a l procedure (49) the parameters , p^, and a are estimated with the requirement that k

k

k

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

k

Z e , i

=

min

k=l,2,

i

N (reactions)

(44)

llc

and £ e,. = min i=l,2,....,M (substituents) (45) k This procedure usually gives a set of o° for which the s i g n i f i cance of the correlations i s better. Obviously the o° values w i l l depend on the data bank and may change as the data bank expands. An important advantage i s the rigorous definition of the reaction types that are represented by this scale of parameters. The dissociation of phenols and anilines does not obey the simple Hammett equation. A new scale of a ~ was proposed (4, 19) for this type of reaction, based on the argument that a strong interaction exists between an electron withdrawing group and the reactive site. This interaction was considered to result from a direct conjugation of the substituent with the reaction center. No theoretical basis for this effect was offered. Also, a ~" i s applicable only for electron withdrawing groups; o had to be used for electron donating groups (19). This indicates that a " cannot represent a single interaction mechanism. A reverse phenomenon occurs in electrophilic aromatic substitutions: they are more sensitive to electron donating substituents than to electron withdrawing substituents. A a scale was therefore defined from studies on the solvolysis of dimethylphenylcarbinyl chlorides i n 90 per cent aqueous acetone (52, 53). Just as there i s a discrepancy between a ~ and a , so there i s a discrepancy between a and a for strong electron donating groups but not for electron withdrawing groups. As a i s an electronic parameter, one can suspect that i t can be separated into inductive, polar, and resonance (i.e., mesomeric) effects. Separation assumes that the effects are indeed independent and that appropriate model systems can be identified i n which these effects can be isolated (232). Several attempts have been made to achieve the separation. It was assumed that o represents the inductive and resonance effects i n an additive fashion (43, 61, 62) with equal weights 1 K

p

p

p

p

p

p

+

p

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

34

COMPUTER-ASSISTED DRUG DESIGN

a

a

=

p

I

+ a

(46)

R

where i s the inductive and a the resonance substituent constant. As resonance effects are different for meta substituents but the inductive effects remain practically the same, the r e l a tion between the two contributions for o can be written as R

m

°m

=

°i +

R

R

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

p

p

p

R

R

R

R

R

log(£ ) - pjOj + p a (48) o As a multiparametric equation, i t requires more precise measurements and larger samples to attain s t a t i s t i c a l v a l i d i t y . The variations i n o obtained from different molecular systems and their small values indicate the inadequacy of such separations to construct a r e l i a b l e a . A more general way to express the separation into inductive and resonance contributions was proposed by Swain and Lupton (72). They claimed that any kind of electronic substituent constant can be represented as R

R

k

R

R

a

-

f «F + r*l? + i

(49)

where F represents the f i e l d constants and R the resonance constants. The constant jl was added i n order not to overemphasize the relative weight of the unsubstituted compound i n the leastsquares f i t t i n g procedure. In fact, the values of the residual constant i^ are very close to zero.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

2.

An interesting approach (73) i n which the parameters tum mechanical methods. The F/r.. and resonance combined o

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

a

¥/r

=

±i

ij

35

Structure-Activity Relationships

OSMAN ET AL.

"

+ Mqjj

±i

F

l

/

r

was proposed by Devar and Grisdale were obtained by semiempirical quanseparation was into electrostatic, with inductive effects (Mq-n and

ij

+

M , 7 r

(50) ( 5 1 )

ij

where r^. i s the distance between atoms 1 and q ^ i s the charge overlap, and TT.. the TT-system charge overlap. This model contains an oversimplified representation of the electrostatic term and may lack the desired physical meaning. This approach i s different from other definitions of a parameters i n that i t can be improved by a better definition of the terms i n equations 50 and 51. Such definitions should follow the basic physical principles of the model and can be rigorously represented by quantum chemical formalisms. 2.

Parameters representing steric effects

In the early 1950s Taft (10) outlined a sound quantitative basis for the estimation of steric effects and for separating them from polar and resonance effects. This derivation follows the standard extrathermodynamic approach and i s therefore empirical. The definition of steric substituent constants i s closely related to polar substituent constants, for they are obtained from the same reference system (10). The polar substituent constants, however, have been shown to arise from electronic effects, and they strongly correlate with the inductive substituent constants (10, 43, 61). aj

=

0.45

a*

(52)

where a-j- i s the inductive and a* the polar substituent constant. The steric substituent constants, E , i s defined as the ratio of rate constants of acid hydrolysis of substituted and unsubstituted acetates. g

+

OH H90/H\ 1

RCOOR

R—

C— I 0H

OR"

= ±

RC00H + R'OH

(53)

o

(54)

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

36

COMPUTER-ASSISTED DRUG DESIGN

where k and k are the rate constants for the acid catalyzed hydrolysis of the substituted and unsubstituted esters, respectively. The reference molecule for which the steric substituent constant i s zero i s therefore the ester of acetic acid; consequently = 0. In this procedure, i t i s assumed that (a) the relative free energy of activation (i.e., the difference between the free energy of activation of the substituted ester and the unsubstituted one) reflects only the steric effects of the substituent on the rate of acid hydrolysis of esters; and (b) the steric substituent constant i s independent of R and of solvent. The v a l i d i t y of these assumptions was tested by applying the derived s t e r i c substituent constants to reactions i n which the transition states resembles that of the acid hydrolysis of esters. It was found that very few reactions obey equation 54. These are exemplified by the acid catalyzed methanolysis of 2-naphthyl esters i n methanol (86) and the reaction of 2-alkylpyridines with methyl iodide (87) and with trimethylboron (88) i n nitrobenzene. The paucity of reactions that depend solely on steric effects i s not surprising. To include electronic contributions, Pavelich and Taft (89) proposed equation 55 Q

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

v

log(k_) = p*a* + s E (55) k 0 Many reaction obey equation 55 (90) implying that the steric effect can be treated as an extrathermodynamic parameter. Realizing the shortcomings of the steric substituent constants, several workers designed other scales, each of which represents a specific component of the overall steric effect. Charton (98) defined a steric parameter U as the difference in van der Waals r a d i i of a substituent X and hydrogen s

c

K

D

x

r

r

r

- vx - vh - vx - i '

2

56

< >

The advantage of this definition of substituent constants i s that they are free of the electronic effects that are present i n E (see below, section C 2 ) . Their use i s limited to symmetrical substituents, such as CHo, l 3 (!•©., XY^). In asymmetric groups the definition of the radius r i s not possible. The similarity of these parameters to the E scale would suggest similar problems, but since they are not based on specific experimental measurements, improvement of the scale i s more d i f f i c u l t . The steric parameters E introduced by Unger and Hansch (99) are simply a shift of the original scale of E . In the former, E = 0 i s for the hydrogen atom rather than for the methyl as i n the latter scale. The connectivity indices x and x (102, 103), quantitatively characterize the size of the molecule and the degree of branching. In that sense, and also because they are derived from a theoretical procedure (104), they lack the usual extrathermodynamic meaning. The strong correlation of X with molar r e f r a c t i v i t y , M , c c

v

g

e

e

g

y

R

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

2.

OSMAN ET AL.

Structure-Activity Relationships

37

suggests that these parameters measure the general steric bulk. The minimal steric difference (MSD) i s another example of a s p e c i f i c a l l y designed s t e r i c constant (105) i n which the parameters are defined as the non-overlapping volume of a certain molecule with a standard molecule possessing the biological a c t i v i t y under study. The reference molecule i s usually the natural substrate, which often must be a r b i t r a r i l y chosen. For conformat i o n a l ^ f l e x i b l e molecules the minimum energy conformations are chosen. This eliminates considerations of other conformers that may be important. Further, this method does not take into consideration that the steric interaction may cause a conformational change i n the molecule or cause a change i n i t s reactivity. The subjective way by which the molecules are superimposed on the reference molecule i s also a shortcoming of the method. This method, however, offers a potential solution to the problem of different a c t i v i t i e s of stereoisomers. A promising approach to the development of steric substituent parameters, STERIMOL, has been presented by Verloop (106). Concluding that a single steric substituent parameter i s unable to account for a l l the steric effects that influence a c t i v i t y , he devised five parameters to describe the length and various widths in well defined directions of the substituent. The length, L, i s defined as the longest axis of the substituent from i t s point of attachment. This parameter i s i n many respects equivalent to the length of a substituent, defined by Bowden and Young (107). The other four parameters, B^-B^, are related to the width of the substituent. B^ represents the minimum width much i n the same sense as the usual Taft's E (101) or Charton's U (98). The minimal width represents the tendency of conformationally f l e x i b l e substituents to change their conformation i n a way that minimizes the steric interaction. Thus, the smallest protruding group ( i . e . , the minimal width) w i l l face the region where a maximal s t e r i c interaction occurs. The other width parameters are derived so that the four B parameters would measure the width i n four rectangular directions. The major problem of this method remains the determination of the conformation of a f l e x i b l e substituent for which the parameters w i l l be determined. Usually the most reasonable conformation i s chosen, i.e., the one of minimum energy, but in some cases, e.g., long hydrocarbon chains, more compact conformations are preferred because differences i n energy are not too large and environmental effects may stabilize the compact geometry. From the five steric parameters the degree of deviation from spheri c a l shape may be estimated by inspection of the ratios L/B^ and B /B^ (i.e., the ratio of length to minimal width and maximal to minimal width). The largest deviations observed for the 243 substituents that have been compiled (106) are L/B-^9 and B^/B^. This method results i n different sets of parameters for geometrical isomers around a non-flexible bond (e.g., E and Z isomers around a double bond). By defining the relative relationship of two of the parameters as orthogonal or opposite-colinear, a g

4

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

38

COMPUTER-ASSISTED DRUG DESIGN

distinction can be made between different stereoisomers.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

3.

Parameters representing hydrophobic interactions

The analysis of the parameters representing the effect of the medium i n terms of extrathermodynamical relations has shown (see above, section A.2) that the hydrophobic substituent constant TT depends on the molecules from which i t i s derived. For example, hydrophobic constants derived from the octanol/water partition coefficients of aromatic molecules d i f f e r from those obtained from aliphatic molecules (112). Collander's equation (111) provides the empirical basis for the evaluation of logP values for the same molecule i n different solvents. However, solvents with markedly different solvation properties (e.g., hydrogen bonding a b i l i t y ) do not conform to Collander's equation (see below, section C.3). It has been shown by Tute and collaborators (228) that the theoretical evaluation of logP on the basis of additivity principles can lead to misleading results for certain molecules (e.g., heterocyclics, s t e r i c a l l y crowded or conformational^ f l e x i b l e molecules). This d i f f i c u l t y has been recently rationalized for r i g i d structures (229). Experimentally measured logP values are therefore more reliable than those estimated from component ir values• Other molecular properties have been also proposed to model the hydrophobic interactions. The parachor, which i s related to the surface tension of a compound (139, 140) represents mainly the intermolecular interactions i n a l i q u i d . The Hildebrand-Scott s o l u b i l i t y parameter, 6, (141) i s related to intermolecular van der Waals forces and the closely related molar attraction constant, F, i s obtained by multiplying 6 by the molar volume (142). The partition coefficient between two solvents can be obtained from the s o l u b i l i t y parameters and the molar volumes of the solute and the solvents (193). This relationship i s based on regular solution theory (194) and the assumption that the p a r t i a l molar volumes of the solute i s not different from i t s molar volume. Recently this has been c r i t i c i z e d and a new derivation was proposed (195) i n which the p a r t i a l molar volumes are taken into account. The molar r e f r a c t i v i t y , MR, i s related to dispersion forces and can be obtained as a sum of the p a r t i a l molar r e f r a c t i v i ties assigned to atoms and bonds (140, 143). These parameters have been compared (144) to establish their relative applicability to correlations with biological activity. The conclusion was that logP and molecular r e f r a c t i v i t y were the best parameters. Parameters obtained from high pressure l i q u i d chromatography (144, 145, 146) and from thin layer chromatography (147) have also been used.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

2.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

C.

39

Structure-Activity Relationships

OSMAN ET AL.

The physicochemical basis of QSAR parameters

The Impressive success of the Hammett equation i n correlating l i t e r a l l y hundreds of observed properties (17) (e.g., rate and equilibrium constants, spectroscopic properties, etc.) may be attributable to the multitude of interaction mechanisms that i s implicitly embedded i n the values of a. The v a l i d i t y of the sepa r a b i l i t y and additivity axioms used i n the derivation of extrathermodynamic relationships i s confirmed by the a b i l i t y to separate experimentally multiple Interaction mechanisms (e.g., inductive and resonance (19, 20, 21), polar and steric (10), enthalpic and entropic (22)). This separation fostered significant progress in the application of quantitative structure-activity relationships to the study of chemical mechanisms. For these relationships can now be expressed i n terms of more basic properties of the molecules under study. It i s assumed that the molecular properties responsible for biological a c t i v i t y can be separated into hydrophobic, electronic and steric effects, a l l of which are independent. It i s further assumed that the hydrophobic effects are f u l l y described by the parameter ir (23, 24, 25), the electronic effects by a (1, 4, 26), and the steric effects by E (10, 27). The relationship between biological a c t i v i t y and the parameters i s expressed by equation 57 (28). g

BA

•

air + pa + s E + const. g

(57)

Higher order terms i n ir must often be included i n the equation (29, 20) which then becomes BA

-

2

air + bir + pa + s E + const. g

(58)

logP ( i . e . , log of the octanol/water partition coefficient) i s frequently interchanged with ir. Equation 58 i s the most widely used one i n QSAR. The model for equation 58 can be considered only as a zero order approximation. Proof, or at least substantial indication, i s needed for the assumption that hydrophobic interactions are well represented by octanol/water partition coefficients. Moreover, the nature of the hydrophobic effect i s complicated (see below), and ir (or logP) may be concealing a host of interactions (e.g., solute-solvent, substituent-molecule)• Electronic effects, although relatively well understood i n chemical systems (mainly due to the successful separations of effects), have a vague meaning i n biological systems because the mechanism of interaction of the drug with the biological system i s not known. Several sites on the drug may be important for the interaction, and more than one electronic parameter may be needed to account for the interaction. Further, overall chemical reactivity i s not necessarily a simple sum of the r e a c t i v i t i e s at these several sites. Most

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

40

COMPUTER-ASSISTED DRUG DESIGN

problematic are the steric parameters. They lack the property of additivity, and being related to the bulkiness of a substituent, they lack directional information, e.g., they cannot account for stereospecific interactions. These uncertainties inherent i n the interpretation of the physical meaning of the parameters limit the scope of mechanistic conclusions from the correlations. Most importantly, a lack of correlation with a certain parameter cannot be interpreted to mean that the type of interaction linked to that parameter i s not relevant to biological activity. A fundamental requirement for any correlation i s that a qualitatively constant mechanism exists. For example, i n kinetic studies, the rate determining step must be the same for a l l molecules, and more importantly, the transition state for the reaction for a l l molecules must be of the same type. The same demand of biological data means that, for example, the drugs bind to the same receptor through the same types of interactions. An apparent lack of correlation may be due to the fact that more than one mechanism can bring about the same effect. The analysis of the deviations could identify differences i n mechanism within a series of compounds or differences i n the effects of substituents on the reactivity of specific compounds i n this series. Pervasive i s also the problem of parameter intercorrelation. To what extent, for example, do hydrophobic parameters depend on electronic changes i n the molecule? Or how much does the steric parameter, being related to the size of a substituent, contribute to the l i p o p h i l i c i t y of the molecule? Without understanding of the physicochemical basis of the parameters used i n QSAR i t i s impossible to assess their significance and the v a l i d i t y of the models from which they are derived. In subsequent sections we discuss the physicochemical basis of these parameters. 1.

The electronic substituent

constant

The numerous reactions and physical properties that can be correlated with electronic substituent constants suggest that they reflect a basic mechanism for the effect of the substituent on the reaction or the property. Many reactions were correlated by the Hammett equation, such as electrophilic (4, 31, 32, 33), nucleop h i l i c (4, 34) and radical (35, 36, 37). Spectroscopic properties, such as infrared and ultraviolet absorption frequencies and i n tensities (38)• nuclear magnetic resonance shifts of various nuclei, e.g., *H, F , C (39), and mass spectroscopic ionization potentials, fragmentations and distributions (40) were also correlated. Enzymological (41, 42) and pharmacological observations (9) were also correlated with electronic substituent constants. A discussion of the acceptable range of the Hammett equation, the treatment of deviations, and the meaning of the separation of interaction mechanism i s of prime importance i n assessing the contribution of electronic effects to biological a c t i v i t y . 1 9

13

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

2.

Structure-Activity Relationships

OSMAN ET AL.

41

A contribution to the v e r i f i c a t i o n of the separability of inductive and resonance effects comes from the thermodynamic approach (74). Since AG°

= -2.3RTlogK

(59)

we can write the Hammett equation as AG°

-

-2.3RTpa

(60)

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

Assuming that the free energy AG° i s separable into inductive and resonance free energies, we can write AG°

=

AG| + AG£

=

at T

z

+ a t R

(61)

R

where a. i s the substituent constants and jt the transmission coefficient of the specific effect. Combining equations 60 and 61 we can write a

f c

I I

+

=

^R

2

- *3RTpa

(62)

Since the transmission coefficients t j and t are assumed to be independent of the substituent i n a reaction where only the substituents are changing (the reaction conditions remain the same), the ratio between the transmission coefficients i s a constant R

^ t

=

b

(63)

I

Substituting equation 63 into equation 62 and rearranging terms we obtain equation 64 t

T

a +a *b T

p

0

•

( 6 A )

It immediately becomes evident that although we assumed the existence of two independent effects (i.e., inductive and resonance), under certain conditions this relationship can be expressed by a single p identified as (tj/T) and a single a identified as ( 2~3R ^* Before proceeding with the analysis of the conditions 'under which equation 64 i s v a l i d , we note the remarkable similarity of this equation to the equations proposed by Yukawa and Tsuno (75) and by Yoshioka, Hamamoto and Kubota (76), equations 65 and 66. These equations were offered to express the correlation i n electrophilic and nucleophilic processes, respectively, in which direct conjugation was of importance.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

42

logJL- = p(a

- a ))

(65)

logJL. = (a ^ + r(o - - a ))

(66)

K

+ r(a

ffi>p

p

+

o p

m

p

p

p

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch002

*o in equation 64, If we identify r i n equations 65 and 66 as b "273R the argument (75) that p and r i n equations 65 and 66 are independent parameters seems to be invalid. In fact a claim has been made that p and r (77, 78) are linearly dependent which i s confirmed by equation 63. I t should be noted that whereas equations 65 and 66 were proposed on a purely empirical basis i n order to improve the correlation i n directly conjugated systems, equation 64 resulted from the assumption of the separability of the inductive and resonance effects expressed i n equation 62. The analysis of equation 64 offers important insight into the nature of p and a i n the Hammett equation. Although the correct general dependence of p on temperature, as predicted from the isokinetic relationship between the enthalpy and the entropy of a reaction i s (1, 79, 80) P

=

where f , g , a n d e a r e t h e e m p i r i c a l p o t e n t i a l p a r a m e t e r s and r i s t h e non-bonded d i s t a n c e . One s u c h t e r m i s e n t e r e d f o r e a c h r , a l t h o u g h f o r most c a l c u l a t i o n s , t h o s e t e r m s f o r r g r e a t e r t h a n a s p e c i f i e d minimum ( e . g . , 10A) a r e s k i p p e d .

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

3.

85

Molecular Mechanics

DUCHAMP

Ehb i s a h y d r o g e n bond e n e r g y t e r m , m o d i f i e d f r o m t h e d e f i n i t i o n o f S c h r o e d e r and L i p p i n c o t t (11), t o f u n c t i o n w i t h one p o t e n t i a l parameter. b e a

E n i s an o u t - o f - p l a n e deformation energy Q 2 ) ( f o r bending a t sp2 p l a n a r h y b r i d i z e d atoms), d e f i n e d a s 0

where f i s a n e m p i r i c a l p o t e n t i a l p a r a m e t e r , and D i s t h e p e r p e n d i c u l a r d i s t a n c e f r o m t h e s p atom t o t h e p l a n e d e f i n e d by t h e t h r e e atoms bonded t o i t . One s u c h t e r m i s e n t e r e d f o r e a c h s p atom bonded t o t h r e e o t h e r atoms. 2

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch003

2

E

tor

i s a

E

t o r s l o n a

tor

=

v

^ ( 1

£ n

s t r a i n energy term, d e f i n e d a s ±

c o s

n

}

* »

where v . . . v a r e e m p i r i c a l p o t e n t i a l p a r a m e t e r s , and 4 i s t h e t o r s i o n a n g l e . By c h o o s i n g a p p r o p r i a t e n, t h e p r o p e r f o r m o f t h e p o t e n t i a l i s s e l e c t e d . An e x p r e s s i o n l i k e t h i s i s entered f o r each t o r s i o n angle. l s

n

E ^ i s an e l e c t r o s t a t i c i n t e r a c t i o n energy term, d e f i n e d a s E

dd •

K

«iy

D r

ij>

where K i s a s c a l i n g f a c t o r , D i s a damping f a c t o r a n a l o g o u s t o t h e b u l k d i e l e c t r i c c o n s t a n t , and q i and q-j a r e t h e c h a r g e s o n atoms i and j s e p a r a t e d by d i s t a n c e r . . . A t e r m i s e n t e r e d f o r e a c h p a i r o f c h a r g e d atoms. Since i t i s a completely computational technique, molecular m e c h a n i c s r e q u i r e s no sample and a l l o w s t h e u s e r t o i n t r o d u c e c a l c u l a t i o n a l t o o l s not p o s s i b l e f o r real molecules. F o r e x a m p l e , t h e i n t r o d u c t i o n o f " e x t r a p o t e n t i a l s " (13) i s p a r t i c u l a r l y u s e f u l when m o l e c u l a r c o n f o r m a t i o n s o t h e r t h a n t h e minimum e n e r g y one must be s t u d i e d . E x t r a p o t e n t i a l s may be added w h i c h make i t p r o h i b i t i v e l y e x p e n s i v e ( i n e n e r g y t e r m s ) f o r a m o l e c u l e n o t t o assume a s t r u c t u r a l f e a t u r e . The minimum energy conformation o f the molecule s u b j e c t t o the c o n s t r a i n t s imposed b y t h e e x t r a p o t e n t i a l s may be o b t a i n e d by m i n i m i z i n g t h e t o t a l e n e r g y -- s t r a i n e n e r g y p l u s e x t r a p o t e n t i a l e n e r g y . J

E

E

total " strain

+

E

extra

By c o m p a r i n g t h e s t r a i n e n e r g y o f t h e m o l e c u l e s o m i n i m i z e d w i t h t h e s t r a i n e n e r g y o f a m o l e c u l e m i n i m i z e d f r e e o f any e x t r a p o t e n t i a l s , the energy c o s t o f assuming a c o n s t r a i n e d c o n f o r m a t i o n may be s t u d i e d .

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch003

86

COMPUTER-ASSISTED DRUG DESIGN

M o l e c u l a r m e c h a n i c s i s n o t w i t h o u t i t s c o m p l i c a t i o n s , some q u i t e s e r i o u s i f one i s i n t e r e s t e d i n v a l i d and a c c u r a t e r e s u l t s . I t i s a t e c h n i q u e where q u a l i t y r e s u l t s a r e o b t a i n e d o n l y i f one u s e s a w e l l d e s i g n e d s e t o f p o t e n t i a l p a r a m e t e r s and d o e s a q u a l i t y c a l c u l a t i n g j o b . Most m o l e c u l a r mechanics advocates have f a i l e d t o i n f o r m o t h e r s c i e n t i s t s o f t h e c r i t i c a l need t o v e r i f y p o t e n t i a l parameters f o r the types o f molecules being c a l c u l a t e d . The b a l a n c i n g o f t h e s e e m p i r i c a l p a r a m e t e r s i s a l s o e x t r e m e l y i m p o r t a n t -- c h a n g i n g one p a r a m e t e r q u i t e o f t e n r e s u l t s i n a need t o c h a n g e s e v e r a l o t h e r s i n o r d e r t o r e b a l a n c e t h e s e t , s i n c e the p o t e n t i a l s a r e not orthogonal t o each o t h e r i n p a r a m e t e r s p a c e . M o l e c u l a r m e c h a n i c s p o t e n t i a l s e t s have been d e v e l o p e d t o p r o d u c e a c c u r a t e r e s u l t s i n c e r t a i n a r e a s , i n c l u d i n g m o l e c u l a r s t r u c t u r e , h e a t s o f f o r m a t i o n , and v i b r a t i o n a l s p e c t r a . When c a l c u l a t i n g m o l e c u l a r s t r u c t u r e , i t i s i m p o r t a n t t o u s e p o t e n t i a l p a r a m e t e r s w h i c h have been d e v e l o p e d to produce a c c u r a t e m o l e c u l a r s t r u c t u r e s . The m a t h e m a t i c a l n a t u r e o f t h e e n e r g y m i n i m i z a t i o n c a l c u l a t i o n l e a d s t o c a l c u l a t i o n a l p r o b l e m s . T h e r e i s no known m a t h e m a t i c a l method f o r o b t a i n i n g a l l p o s s i b l e e n e r g y m i n i m a i n t h e p a r a m e t e r s p a c e o f a m o l e c u l e . T h e r e a r e good m a t h e m a t i c a l t e c h n i q u e s f o r m o v i n g d o w n h i l l i n e n e r g y t o a minimum, b u t t h e r e i s no m a t h e m a t i c a l way o f d e t e r m i n i n g i f t h e minimum reached i s g l o b a l , t h a t i s , i f i t corresponds to the lowest e n e r g y c o n f o r m a t i o n . I f a l l low e n e r g y c o n f o r m a t i o n s o f a m o l e c u l e a r e t o b e e x p l o r e d , a t r i a l and e r r o r s e a r c h i n g p r o c e s s m u s t be u s e d . Such t e c h n i q u e s a r e v e r y c o s t l y i n c o m p u t e r t i m e because o f the c o m b i n a t o r i a l a s p e c t s o f the problem. In f a i r l y f l e x i b l e m o l e c u l e s , t h e number o f c o m b i n a t i o n s w h i c h must be e x p l o r e d i s s o v a s t , t h a t a p p r o x i m a t i o n s a r e f r e q u e n t l y made w h i c h a r e s o d r a s t i c t h a t one must wonder i f i m p o r t a n t c o n f o r m a t i o n s have n o t been m i s s e d . F i n a l l y , t h e n a t u r e o f t h e f i n a l m i n i m i z a t i o n p r o c e s s must be n o t e d i n e v a l u a t i n g t h e q u a l i t y o f a r e s u l t f r o m m o l e c u l a r mechanics. S e a r c h i n g i s f r e q u e n t l y done by h o l d i n g bond d i s t a n c e s and a n g l e s f i x e d and o n l y v a r y i n g t o r s i o n a l a n g l e s , t h e r e b e i n g no o t h e r c a l c u l a t i o n a l l y f e a s i b l e way t o h a n d l e t h e p r o b l e m i n many c a s e s . I t i s w e l l known e x p e r i m e n t a l l y and t h e o r e t i c a l l y t h a t s m a l l d i s t o r t i o n s i n bond d i s t a n c e s and e s p e c i a l l y i n bond a n g l e s f r e q u e n t l y can l o w e r ( g r e a t l y ) t h e s t r a i n e n e r g y o f a g i v e n c o n f o r m a t i o n . E x p e r i e n c e i s t h a t when atoms a r e a l l o w e d t o v a r y f r e e l y (bond d i s t a n c e s and a n g l e s a r e a l l o w e d t o c h a n g e ) conformational energy changes o f over 5 kcal/mole are not uncommon, and a d i f f e r e n t e n e r g y o r d e r i n g o f low e n e r g y c o n f o r m ations frequently r e s u l t s . Unless a f r e e minimization c a l c u l a t i o n has been p e r f o r m e d , r e p o r t e d m o l e c u l a r m e c h a n i c s e n e r g y v a l u e s must be r e g a r d e d w i t h s u s p i c i o n . Other m o l e c u l a r mechanics c o m p l i c a t i o n s r e s u l t from the n a t u r e o f t h e s t r a i n e n e r g y m o d e l . The e n e r g y i s u s u a l l y e v a l u a t e d f o r t h e m o l e c u l e i n a vacuum, t h a t i s , f r e e o f c o n t a c t s

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch003

3.

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w i t h o t h e r m o l e c u l e s . I f t h e c r y s t a l s t r u c t u r e i s known, i n t e r a c t i o n s i n t h e c r y s t a l may be s i m u l a t e d . A r e a s o n a b l y good way o f s i m u l a t i n g a m o l e c u l e i n s o l u t i o n by m o l e c u l a r m e c h a n i c s i s y e t t o be d e v e l o p e d , however. A l s o , t h e r m a l e f f e c t s a r e accounted f o r only very i n d i r e c t l y i n the empirical c a l c u l a t i o n o f s t r a i n e n e r g y . " S t r a i n e n e r g y " a s c a l c u l a t e d by m o l e c u l a r mechanics i s not the f r e e energy o f the molecule i n a given c o n f o r m a t i o n . S t r a i n e n e r g i e s c o r r e s p o n d more c l o s e l y t o e n t h a l p y d i f f e r e n c e s (1_0). Whereas t h e e n t h a l p y d i f f e r e n c e between two c o n f o r m a t i o n s o f a m o l e c u l e i s s i g n i f i c a n t and important, i t i s t h e f r e e energy d i f f e r e n c e which determines t h e r e l a t i v e p e r c e n t a g e o f t h e two c o n f o r m e r s o c c u r i n g a t a g i v e n t e m p e r a t u r e . T h i s i s e s p e c i a l l y i m p o r t a n t t o remember when c o r r e l a t i n g p e r c e n t a g e s o f c o n f o r m e r s d e t e r m i n e d e x p e r i m e n t a l l y with t h e percentages p r e d i c t e d from m o l e c u l a r mechanics energy d i f f e r e n c e s . Combining M o l e c u l a r Mechanics and C r y s t a l S t r u c t u r e A n a l y s i s T h e r e a r e a number o f a d v a n t a g e s t o u s i n g a combined molecular mechanics/crystal s t r u c t u r e a n a l y s i s approach t o studying three-dimensional molecular s t r u c t u r e f o r drug design p u r p o s e s . C r y s t a l s t r u c t u r e r e s u l t s c a n be u s e d t o v e r i f y and develop molecular mechanics p o t e n t i a l parameters. M o l e c u l a r m e c h a n i c s c a n be u s e d t o t e s t f o r c r y s t a l s t r u c t u r e " a r t i f a c t s " , that i s to t e s t i f a f e a t u r e observed i n a c r y s t a l s t r u c t u r e i s an i n h e r e n t p r o p e r t y o f t h e m o l e c u l e o r i f i t r e s u l t s f r o m t h e way i n w h i c h t h e m o l e c u l e i s i n f l u e n c e d by i t s n e i g h b o r s i n t h e c r y s t a l . M o l e c u l a r m e c h a n i c s r e s u l t s c a n be u s e d t o extrapolate crystal structure results to non-crystalline s i t u a t i o n s . And p e r h a p s m o s t i m p o r t a n t , m o l e c u l a r m e c h a n i c s r e s u l t s a r e more a p t t o be v a l i d i f backed up by e x p e r i m e n t a l data from c r y s t a l s t r u c t u r e a n a l y s i s . I f a s e t o f p o t e n t i a l parameters can c o r r e c t l y reproduce the experimental r e s u l t s f o r a molecule i n t h e c r y s t a l , t h i s s e t o f p o t e n t i a l parameters should also c a l c u l a t e meaningful r e s u l t s f o r t h i s molecule i n o t h e r s i t u a t i o n s . One knows a l s o t h a t t h e c o n f o r m a t i o n o b t a i n e d by f r e e m i n i m i z a t i o n f r o m t h e c r y s t a l c o n f o r m a t i o n i s a l o w e n e r g y c o n f o r m a t i o n -- i t i s n o t a l w a y s t h e l o w e s t e n e r g y c o n f o r m a t i o n , b u t i s u s u a l l y w i t h i n 2-3 k c a l / m o l e o f t h e l o w e s t . T h i s c a n be e x t r e m e l y v a l u a b l e i n f o r m a t i o n . T h e e n e r g y a c c e s s i b i l i t y o f a p r o p o s e d a c t i v e c o n f o r m a t i o n may be e v a l u a t e d by c o m p a r i n g i t s e n e r g y w i t h t h e e n e r g y o b t a i n e d by f r e e m i n i m i z a t i o n f r o m t h e c r y s t a l c o n f o r m a t i o n , t h u s a l l e v i a t i n g t h e need t o s e a r c h c o n f o r m a t i o n a l s p a c e f o r a g l o b a l minimum e n e r g y . P o t e n t i a l Parameter

Verification

As m e n t i o n e d a b o v e , when a s e t o f p o t e n t i a l f u n c t i o n p a r a m e t e r s i s t o be u s e d i n m o l e c u l a r m e c h a n i c s c a l c u l a t i o n s on

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch003

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a c e r t a i n c l a s s o f molecules, i t i s important to v e r i f y that t h e p a r a m e t e r s work f o r t h a t c l a s s o f m o l e c u l e s . The o n l y way t o d o t h i s i s t o compare c a l c u l a t e d m o l e c u l a r m e c h a n i c s r e s u l t s w i t h e x p e r i m e n t a l r e s u l t s . F o r m o l e c u l e s t h e s i z e o f most drugs, the o n l y s t r u c t u r a l experimental r e s u l t s which a r e a c c u r a t e enough f o r t h i s a r e c r y s t a l s t r u c t u r e r e s u l t s . When making such comparisons to v e r i f y a s e t o f p o t e n t i a l f u n c t i o n s , m o l e c u l e s o f s i m i l a r s i z e and c h e m i c a l t y p e t o t h o s e b e i n g s t u d i e d must be u s e d . E x p e r i m e n t a l l y i t i s w e l l known, f o r e x a m p l e , t h a t t h e a m i d e g r o u p i n f o r m a m i d e i s a p o o r model f o r t h e a m i d e g r o u p i n p e p t i d e s ( 1 4 ) . E x p e r i e n c e has shown u s t h a t m o l e c u l a r m e c h a n i c s r e s u l t s sTiôuld be compared w i t h low t e m p e r ature crystal structure results i f at a l l possible. If this i s not done, i t i s f r e q u e n t l y d i f f i c u l t to d i s c e r n whether d i f f e r e n c e s i n c a l c u l a t e d and e x p e r i m e n t a l m o l e c u l a r p a r a m e t e r s a r e due t o p o t e n t i a l p a r a m e t e r d e f i c i e n c i e s o r t h e r m a l o r d e t e r i o r a t i o n e f f e c t s i n t h e c r y s t a l . E x p e r i e n c e has a l s o shown t h a t f o r meaningful comparisons, experimental m o l e c u l a r parameters f r o m t h e c r y s t a l must b e compared w i t h c a l c u l a t e d p a r a m e t e r s o b t a i n e d by m i n i m i z a t i o n i n t h e c r y s t a l . I n a d d i t i o n , i m p o r t a n t p o t e n t i a l p a r a m e t e r s s h o u l d be c h e c k e d a g a i n s t more t h a n one c r y s t a l s t r u c t u r e , p r e f e r a b l y s e v e r a l o f somewhat d i f f e r e n t chemical type. The p o t e n t i a l p a r a m e t e r s w h i c h we employ were d e v e l o p e d o v e r a p e r i o d o f y e a r s use i n c a l c u l a t i n g l a r g e m o l e c u l e s y s t e m s , s u c h a s d r u g m o l e c u l e s . F o r some p a r a m e t e r s , v a l u e s f r o m t h e l i t e r a t u r e (10, 15-21, f o r e x a m p l e ) were r e f i n e d and b a l a n c e d , i n o t h e r c a s e s , new v a l u e s were c h o s e n f r o m s t u d y o f e x p e r i m e n t a l s t r u c t u r a l r e s u l t s . The v a l u e s o f a l l p a r a m e t e r s were r e f i n e d and t e s t e d b y c o m p a r i n g c a l c u l a t e d and o b s e r v e d p a r a m e t e r s f o r l a r g e m o l e c u l e s i n t h e c r y s t a l . The p r o c e d u r e w h i c h we f o l l o w f o r minimizing the molecule i n the c r y s t a l i s t o surround an a s y m m e t r i c u n i t o f m o l e c u l e s i n t h e c r y s t a l w i t h symmetry r e l a t e d n e i g h b o r i n g atoms o u t t o a c e r t a i n maximum d i s t a n c e ( u s u a l l y a r o u n d 10 A n g s t r o m s ) . Then t h e m i n i m i z a t i o n i s c a r r i e d o u t b y h o l d i n g t h e u n i t c e l l p a r a m e t e r s f i x e d and v a r y i n g t h e a t o m i c p o s i t i o n s , w h i l e p r e s e r v i n g t h e symmetry o f t h e s p a c e g r o u p . T h i s s i m p l e method p r o d u c e s good s t r u c t u r a l r e s u l t s i f c a l c u l a t i o n o f s t r u c t u r a l parameters i s d e s i r e d . To save c o m p u t e r t i m e , t h e f i r s t few i t e r a t i o n s i n t h e m i n i m i z a t i o n a r e r u n w i t h o n l y hydrogen atom p o s i t i o n s v a r y i n g , s i n c e hydrogen p o s i t i o n s f r o m x - r a y a n a l y s i s a r e p o o r and sometimes need s i z a b l e a d j u s t m e n t . T h i s s i m p l e method w i l l n o t work i f e i t h e r u n i t c e l l p a r a m e t e r s a r e t o be v a r i e d , o r i f a c c u r a t e l a t t i c e e n e r g i e s a r e t o be c a l c u l a t e d . For these purposes, l a t t i c e sums must b e e v a l u a t e d f o r a c c u r a t e r e s u l t s ( 2 2 ) . The a c c u r a c y t o be e x p e c t e d i n s u c h v e r i f i c a t i o n s i s i l l u s t r a t e d i n F i g u r e 3. A c c u r a t e low t e m p e r a t u r e c r y s t a l s t r u c t u r e r e s u l t s o n m o r p h i n e m o n o h y d r a t e (8) a r e compared w i t h r e s u l t s o b t a i n e d by m i n i m i z i n g m o r p h i n e m o n o h y d r a t e i n t h e

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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c r y s t a l as w h i c h were ment w h i c h summarized

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d e s c r i b e d a b o v e . Some o f t h e m o l e c u l a r p a r a m e t e r s p a r t i c u l a r l y hard t o f i t a r e t a b u l a t e d . The agreec a n n o r m a l l y be o b t a i n e d i n s u c h c o m p a r i s o n s i s i n t h e f i g u r e a t t h e lower r i g h t .

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch003

Using M o l e c u l a r Mechanics t o T e s t C r y s t a l S t r u c t u r e Features In t h e c r y s t a l s t r u c t u r e o f N - a c e t y l p h e n y l a l a n y l t y r o s i n e (23) t h e a m i d e g r o u p c o n n e c t i n g t h e p h e n y l a l a n i n e a n d t h e t y r o s i n e was f o u n d t o be c o n s i d e r a b l y n o n - p l a n a r . In p a r t i c u l a r , a s i l l u s t r a t e d i n F i g u r e 4, t h e C-C-N-C t o r s i o n a n g l e a c r o s s t h e a m i d e bond was 1 7 . 7 ° o u t o f p l a n a r . M i n i m i z a t i o n i n t h e c r y s t a l by m o l e c u l a r m e c h a n i c s gave a v a l u e i n good agreement w i t h t h e o b s e r v e d . When t h e m o l e c u l e was m i n i m i z e d f r e e , however, t h e n o n p l a n a r i t y a s i n d i c a t e d by t h e C-C-N-C t o r s i o n a n g l e was r e d u c e d t o 4 . 7 ° , s t i l l s i g n i f i c a n t b u t f a r l e s s t h a n f o u n d i n t h e c r y s t a l . A p p a r e n t l y t h e t h r e e h y d r o g e n bonds w h i c h occur i n the crystal strongly influence the conformation o f the m o l e c u l e i n t h e c r y s t a l . In a case such as t h i s , i t i s important t h a t t h e m o l e c u l a r mechanics p o t e n t i a l s , which a r e used t o t e s t i f a f e a t u r e p e r s i s t s o u t s i d e o f t h e c r y s t a l , be a b l e t o c o r r e c t l y r e p r o d u c e t h é o b s e r v e d f e a t u r e by c a l c u l a t i o n o f t h e m o l e c u l e in the crystal. A n o t h e r example o f t h e u s e o f m o l e c u l a r m e c h a n i c s t o t e s t and i n t e r p r e t f e a t u r e s f o u n d i n c r y s t a l s t r u c t u r e s t u d i e s i s g i v e n by a c o m p a r i s o n o f 19-nor a n d r o s t e n e d i o l a n d 7 - a - m e t h y l 1 9 - n o r a n d r o s t e n e d i o l QJ. T h e i n t r o d u c t i o n o f t h e 7 - a - m e t h y l m o i e t y i n t o 19-nor a n d r o s t e n e d i o l was f o u n d t o i n c r e a s e i t s potency about 4 0 0 - f o l d i n l a b o r a t o r y s t u d i e s . The c r y s t a l s t r u c t u r e s o f t h e two were d e t e r m i n e d by x - r a y d i f f r a c t i o n , a n d t h e c o n f o r m a t i o n s o f t h e Α - r i n g s were f o u n d t o be s i g n i f i c a n t l y d i f f e r e n t , a s shown i n F i g u r e 5. M o l e c u l a r m e c h a n i c s was u s e d t o t e s t w h e t h e r t h e d i f f e r e n c e i n o b s e r v e d c o n f o r m a t i o n o f t h e s e m o l e c u l e s was d u e t o a d i f f e r e n c e i n p r e f e r r e d c o n f o r m a t i o n o r due t o c r y s t a l p a c k i n g . M o l e c u l a r m e c h a n i c s was u s e d t o v a r y t h e c o n f o r m a t i o n u s i n g t h e C ( l ) C(10)-C(5)-C(6) t o r s i o n a n g l e a s a parameter and c a l c u l a t i n g the s t r a i n energy a t each conformation, as i l l u s t r a t e d i n F i g u r e 6 f o r o n e o f t h e m o l e c u l e s . A f r e e m i n i m i z a t i o n was p e r f o r m e d a t e a c h t o r s i o n a n g l e . When t h e e n e r g y was p l o t t e d a g a i n s t t o r s i o n a n g l e ( s e e F i g u r e 7 ) , t h e m i n i m a f o r t h e two m o l e c u l e s were f o u n d t o o c c u r a t t h e same p o i n t . I n f a c t , a s F i g u r e 6 shows, t h e Α - r i n g may v a r y q u i t e a b i t i n i t s o r i e n t a ­ t i o n w i t h r e s p e c t t o t h e r e m a i n d e r o f t h e m o l e c u l e . From t h i s , one may c o n c l u d e t h a t 1) t h e e f f e c t o f t h e 7 - a - m e t h y l on t h e a c t i v i t y o f t h e m o l e c u l e s i s n o t t h r o u g h a n y change i n i n h e r ­ e n t l y p r e f e r r e d c o n f o r m a t i o n , a n d 2) t h e 19-nor a n d r o s t e n e d i o l molecule i s f a i r l y f l e x i b l e . As Figure 5 i l l u s t r a t e s , t h e 7-amethyl group does p r o t r u d e o u t from t h e plane o f t h e m o l e c u l e , and c o u l d d e f i n i t e l y i n f l u e n c e t h i s f l e x i b l e m o l e c u l e t o assume

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch003

COMPUTER-ASSISTED DRUG DESIGN

Figure 3. Comparison of calculated and observed values of selected structural parameters for morphine monohydrate in the crystal. Values listed under expected agreement are for minimization in the crystal in general; values in parentheses are maximum observed deviations.

Figure 4.

Ν-acetyl phenylahnyl tyrosine in the crystal (upper) and minimized free (lower)

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch003

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DOWN C(8)-C(12) Figure 5. X-ray diffraction crystal structure results on 19-norandrostenediol (left) and 7-a-methyl-19-norandrostenediol (right)

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Figure 6. Conformations of the rings of 19-norandrostenediol as the C(l)—C(10)—C(5)—C(6) torsion angle is varied

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch003

2!

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ι

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to

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Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch003

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4-,

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f KCAlA JWOLEJ

i

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120 130 MO TORSION ANGLE (1-10-5-6)

ISO

160

Figure 7. Calculated strain energy vs. C(l)—C(10)—C(5)—C(6) torsion angle in 19-norandrostenediol ffj, R=H) and 7-a-methyU19-norandrostenediol (X, R = CH,)

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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a d i f f e r e n t c o n f o r m a t i o n when i t s i t s o n a r e c e p t o r , j u s t a s i t c e d i t t o assume a d i f f e r e n t c o n f o r m a t i o n i n t h e c r y s t a l . T h i s i n v e s t i g a t i o n has o b v i o u s l y n o t r u l e d o u t m e t a b o l i s m o r t r a n s p o r t e f f e c t s w h i c h may be v e r y i m p o r t a n t i n t h i s c a s e .

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch003

Examples From t h e S t u d y o f A n a l g e s i c s Some e x a m p l e s f r o m o u r r e c e n t s t u d y o f o p i a t e a n a l g e s i c s t r u c t u r e s (8,24) s e r v e t o i l l u s t r a t e f u r t h e r t h e t y p e s o f i n f o r m a t i o n w h i c h a c o m b i n e d a p p r o a c h can p r o v i d e . The a p p r o a c h u s e d i n t h i s s t u d y was 1) a c c u m u l a t e a c c u r a t e c r y s t a l s t r u c t u r e r e s u l t s o n r e p r e s e n t a t i v e compounds b y l i t e r a t u r e s e a r c h and performing c r y s t a l s t r u c t u r e d e t e r m i n a t i o n s , then 2) develop and v e r i f y m o l e c u l a r m e c h a n i c s p o t e n t i a l p a r a m e t e r s f o r use w i t h a n a l g e s i c s , and 3 ) p e r f o r m s t r a i n e n e r g y c a l c u l a t i o n s t o f i n d a c t i v e conformations by comparing d i f f e r e n t chemical s t r u c t u r a l t y p e s w h i c h a c t a t a common r e c e p t o r . The o b j e c t o f t h e s t u d y was t o 1 ) b e t t e r d e f i n e t h e t h r e e - d i m e n s i o n a l r e q u i r e ments o f o p i a t e a n a l g e s i c s , and 2) b e t t e r u n d e r s t a n d t h e o p i a t e r e c e p t o r i t s e l f by i n d i r e c t l y i n v e s t i g a t i n g i t . Although the morphine molecule i s u s u a l l y considered very r i g i d b e c a u s e o f i t s i n t e r l o c k i n g r i n g s , m o l e c u l a r model s t u d i e s had h i n t e d t h a t t h e r e m i g h t be some f l e x i b i l i t y , and t h a t t h i s f l e x i b i l i t y m i g h t be c h a r a c t e r i z e d b y r o t a t i o n a b o u t t h e C ( 1 2 ) C(13) bond ( s e e F i g u r e 3 ) . T o s t u d y t h i s f l e x i b i l i t y by m o l e c u l a r m e c h a n i c s , we u s e d a n " e x t r a p o t e n t i a l " t o c a u s e t h e C(4)-C(12)-C(13)-C(14) t o r s i o n a n g l e t o be c o n s t r a i n e d t o v a r i o u s v a l u e s and d i d a c o m p l e t e m i n i m i z a t i o n a t e a c h c o n s t r a i n e d v a l u e . The r e s u l t i n g p o t e n t i a l w e l l i s p l o t t e d i n F i g u r e 8. I t i s e v i d e n t f r o m t h i s p l o t t h a t t h e r e i s a c o n s i d e r a b l e amount o f f l e x i b i l i t y i n t h e m o r p h i n e m o l e c u l e . The C ( 4 ) C ( 1 2 ) - C ( 1 3 ) - C ( 1 4 ) t o r s i o n a n g l e may be v a r i e d o v e r a 40° r a n g e without i n t r o d u c i n g e x c e s s i v e s t r a i n i n the molecule. As the drawings above the p l o t i n F i g u r e 8 i l l u s t r a t e , t h i s i s an important f l e x i b i l i t y s i n c e i t s t r o n g l y i n f l u e n c e s the t h r e e d i m e n s i o n a l r e l a t i o n s h i p between t h e b a s i c n i t r o g e n and t h e aromatic r i n g , g r e a t l y changing the d i s t a n c e o f the basic n i t r o g e n f r o m t h e p l a n e o f t h e a r o m a t i c r i n g . The c o n c l u s i o n s o f i n t e r e s t h e r e a r e t h a t m o r p h i n e has some f l e x i b i l i t y , and when compared t o o t h e r m o l e c u l e s , i t s a t o m i c p o s i t i o n s must be v a r i e d and s h o u l d n o t b e c o n s i d e r e d r i g i d . The f e n t a n y l m o l e c u l e has c o n s i d e r a b l e f l e x i b i l i t y . I n o r d e r t o s t u d y t h e c o n f o r m a t i o n o f f e n t a n y l a t t h e r e c e p t o r , we matched i t s conformation t o t h a t o f morphine which i s c o n s i d e r a b l y l e s s f l e x i b l e . T o p e r f o r m t h e c a l c u l a t i o n , m o r p h i n e and t h e t e s t m o l e c u l e a r e o v e r l a y e d ( i n t h e c o m p u t e r ) and c o n n e c t e d a t f o u r p o i n t s b y e x t r a p o t e n t i a l s a s shown i n F i g u r e 9. T h r e e p o t e n t i a l s a l i g n t h e a r o m a t i c r i n g , and one m a t c h e s t h e p o s i t i o n o f t h e b a s i c n i t r o g e n . The g r o s s a l i g n m e n t o f t h e two m o l e c u l e s i s done o n o u r c o m p u t e r g r a p h i c s s y s t e m , i n c l u d i n g any l a r g e

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Figure 8. Flexibility of morphine to rotation about the C(12)—C(13) bond

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch003

CD

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co Ci

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s:

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Figure 9. Method used to link morphine to other opiate molecules for conformational matching. The springs represent "extra potentials*' of the form shown at the lower left (E = cd ) 2

Figure 10.

Bestfitfrom conformational matching of morphine and fentanyl

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch003

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c h a n g e s i n m o l e c u l a r c o n f o r m a t i o n . V a r i o u s ways o f m a t c h i n g t h e two t o g e t h e r were t r i e d , i n c l u d i n g m a t c h i n g b o t h a r o m a t i c r i n g s o f f e n t a n y l t o t h e morphine aromatic r i n g . F o r each m a t c h , t h e two m o l e c u l e s a r e m i n i m i z e d s i m u l t a n e o u s l y w i t h a l l x , y , z c o o r d i n a t e s o f a l l atoms b e i n g v a r i e d . T h e e n e r g y m i n i m i z e d i s t h e sum o f t h e s t r a i n e n e r g y o f b o t h m o l e c u l e s a n d t h e e x t r a p o t e n t i a l energy. The r e s u l t s o f t h i s experiment a r e i l l u s t r a t e d i n F i g u r e 10. T h e e n e r g i e s shown a r e t h e d i f f e r e n c e s between t h e c a l c u l a t e d s t r a i n e n e r g i e s f o r t h e m o l e c u l e m i n i m i z e d t o g e t h e r as d e s c r i b e d above, and t h e s t r a i n energy o b t a i n e d when t h e m o l e c u l e i s m i n i m i z e d f r e e o f a l l i n t e r m o l e c u l a r i n t e r a c t i o n s and e x t r a p o t e n t i a l s . The d i s t a n c e s a r e t h e f i n a l l e n g t h s o f t h e " s p r i n g s " shown i n F i g u r e 10. B o t h t h e e n e r g i e s and d i s t a n c e s i n d i c a t e a good f i t . T h e v a l u e s o b t a i n e d f o r t h e e n e r g i e s a n d d i s t a n c e s must be i n t e r p r e t e d somewhat q u a l i t a t i v e l y , s i n c e by c h a n g i n g t h e c o n s t a n t s i n t h e e x t r a p o t e n t i a l s , one c a n go t o h i g h e r e n e r g i e s a n d s h o r t e r d i s t a n c e s o r l o w e r e n e r g i e s and l o n g e r d i s t a n c e s . The c o n c l u s i o n i s t h a t w i t h f e n t a n y l i n t h i s c o n f o r m a t i o n , a r e a s o n a b l y good f i t c a n be o b t a i n e d a t a r e a s o n a b l e e n e r g y , an e n e r g y w e l l w i t h i n t h e r a n g e t h a t m i g h t be e x p e c t e d t o be p r e s e n t i n a d r u g - r e c e p t o r i n t e r a c t i o n . T h e v a r i o u s c o n f o r m a t i o n s o f f e n t a n y l w h i c h have been d i s c u s s e d a r e shown i n F i g u r e 11. Note t h a t t h e p h e n e t h y l g r o u p i s r o t a t e d d i f f e r e n t l y i n t h e matched c o n f o r m a t i o n f r o m b o t h t h e c o n f o r m a t i o n o b t a i n e d by f r e e m i n i m i z a t i o n a n d t h e conformation observed i n the c r y s t a l . When we p e r f o r m e d a c r y s t a l s t r u c t u r e a n a l y s i s on m e p e r i d i n e h y d r o c h l o r i d e , two symmetry i n d e p e n d e n t m o l e c u l e s were f o u n d i n t h e symmetry i n d e p e n d e n t u n i t . T h e two m o l e c u l e s d i f f e r c o n f o r m a t i o n a l l y i n t h e o r i e n t a t i o n o f t h e e t h y l g r o u p . In t h e s t r u c t u r e o f m e p e r i d i n e h y d r o b r o m i d e r e p o r t e d by Van K o n i g s v e l d (25), t h e e t h y l group i s found i n y e t a t h i r d conformation. M o l e c u l a r m e c h a n i c s c a l c u l a t i o n s v e r i f i e d t h a t t h e r e i s no s i g n i f i c a n t e n e r g y d i f f e r e n c e between t h e t h r e e o r i e n t a t i o n s o f t h e e t h y l g r o u p . In a l l t h r e e o b s e r v e d m o l e c u l e s , t h e p h e n y l i s e q u a t o r i a l t o t h e 6-membered r i n g . I t had e a r l i e r been s u g g e s t e d , however, t h a t a n a x i a l p h e n y l o r i e n t a t i o n m i g h t be t h e a c t i v e f o r m ( 2 6 ) . When m i n i m i z e d a s a f r e e m o l e c u l e , t h e e q u a t o r i a l p h e n y l f o r m i s f o u n d t o be f a v o r e d by 0.8 k c a l / m o l e over t h e a x i a l phenyl form, a s m a l l e r energy d i f f e r e n c e than one m i g h t e x p e c t . Both t h e a x i a l phenyl a n d t h e e q u a t o r i a l phenyl conformers were matched t o m o r p h i n e u s i n g t h e 4 - p o i n t m a t c h i n g t e c h n i q u e d e s c r i b e d above. T h e r e s u l t s a r e i l l u s t r a t e d i n F i g u r e 12 w i t h t h e e q u a t o r i a l m a t c h on t h e l e f t a n d t h e a x i a l on t h e r i g h t . B o t h c a n be made t o f i t . T h e f i t f o r t h e a x i a l i s somewhat b e t t e r . The m e p e r i d i n e s t r a i n energy f o r t h e a x i a l match i s 3.6 k c a l / m o l e , w h e r e a s 6.9 k c a l / m o l e was r e q u i r e d f o r a s i m i l a r match i n t h e e q u a t o r i a l c a s e . Both e n e r g i e s a r e d i f f e r e n c e s from t h e lowest energy conformer which i s e q u a t o r i a l . Although

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch003

Figure 12. Bestfitconformations from matching morphine (top) with meperidine equatorial (left) and axial (right) phenyl conformers

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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t h e s e d a t a p o i n t t o t h e a x i a l c o n f o r m e r as b e i n g a b e t t e r m a t c h , t h e c o n c l u s i v e p o i n t a p p e a r s t o be t h e o r i e n t a t i o n o f t h e p r o t o n on t h e b a s i c n i t r o g e n . A f t e r m a t c h i n g , t h e p r o t o n on t h i s n i t r o g e n i s o r i e n t e d i n t h e same way as t h a t o f m o r p h i n e i n t h e a x i a l c a s e , but i n an u n a c c e p t a b l e d i r e c t i o n i n t h e e q u a t o r i a l phenyl case.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch003

B u i l d i n g and T e s t i n g a Model f o r R e c e p t o r

Requirements

I f s t r u c t u r a l i n f o r m a t i o n i s a v a i l a b l e on a number o f m o l e c u l e s w h i c h a r e known t o a c t a t a g i v e n r e c e p t o r , a model f o r t h e r e q u i r e m e n t s o f t h e r e c e p t o r may be d e v e l o p e d . Different methods have been u s e d f o r t h i s ; t h e one we u s e i n v o l v e s e x a c t q u a n t i t a t i v e conformation matching using molecular mechanics. E x t r a p o t e n t i a l s c a n be u s e d t o match c o n f o r m a t i o n s o f more t h a n two m o l e c u l e s a t a t i m e by s i m u l t a n e o u s m i n i m i z a t i o n . I n o u r a n a l g e s i c work, we f r e q u e n t l y have m a t c h e d m o r p h i n e t o two o r t h r e e m o l e c u l e s s i m u l t a n e o u s l y , and have i n t r o d u c e d more e x t r a p o t e n t i a l s t o e x t e n d t h e f i t t i n g r e q u i r e m e n t s beyond t h e f o u r p o i n t s m e n t i o n e d above. The p r i n c i p a l d i s a d v a n t a g e t o m a t c h i n g many m o l e c u l e s s i m u l t a n e o u s l y i s t h a t t h e c o m p u t e r t i m e r e q u i r e d goes up f a s t e r t h a n t h e number o f m o l e c u l e s . T h e t e c h n i q u e , and o u r c o m p u t e r programs, a l l o w a d i f f e r e n t a p p r o a c h t o s i m p l i f y t h e c a l c u l a t i o n s , however. Once t h e s i m u l t a n e o u s m i n i m i z a t i o n o f a number o f r e p r e s e n t a t i v e m o l e c u l e s has a c h i e v e d a good m a t c h a t a number o f p o i n t s , t h e t h r e e - d i m e n s i o n a l c o o r d i n a t e s o f these p o i n t s c o n s t i t u t e a model, which o t h e r m o l e c u l e s a c t i n g a t t h e same r e c e p t o r may be t e s t e d a g a i n s t . To a s s e s s t h e f i t o f a s u b s e q u e n t m o l e c u l e t o t h i s m o d e l , i t i s then s u f f i c i e n t to minimize the molecule s u b j e c t to the cons t r a i n t s imposed by e x t r a p o t e n t i a l s l i n k i n g s i t e s i n t h e molecule to the p o i n t s d e f i n i n g the model; the p o i n t s i n the model b e i n g h e l d f i x e d d u r i n g t h e m i n i m i z i n g p r o c e s s . T h i s c a l c u l a t i o n i s r o u g h l y e q u i v a l e n t i n computer time t o m i n i m i z i n g a single molecule. Computer g r a p h i c s i s e s s e n t i a l i n t h i s t y p e o f work. I n i t i a l m a t c h e s o f m o l e c u l a r c o n f o r m a t i o n s a r e f o u n d by c o m p u t e r g r a p h i c s , r e d u c i n g t h e amount o f c o n f o r m a t i o n a l s e a r c h i n g needed. By v a r y i n g t h e c o n f o r m a t i o n o f m o l e c u l e s v i a i n t e r a c t i v e g r a p h i c s , the chemist can use h i s i n t u i t i o n to g r e a t l y reduce t h e amount o f c o m p u t e r c a l c u l a t i o n s . O t h e r p a p e r s i n t h i s symposium expound f u r t h e r on t h e u t i l i t y o f t h i s v a l u a b l e t o o l in drug design. Conclusions The c o m b i n a t i o n o f c r y s t a l s t r u c t u r e a n a l y s i s and m o l e c u l a r m e c h a n i c s i s a v a l u a b l e t o o l i n d r u g d e s i g n , s i n c e i t can be used to p r o v i d e t h r e e - d i m e n s i o n a l i n f o r m a t i o n which can g r e a t l y h e l p t h e m e d i c i n a l c h e m i s t d e s i g n new m o l e c u l e s w i t h d e s i r a b l e

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch003

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a c t i v i t i e s . C r y s t a l s t r u c t u r e r e s u l t s are not very hard o r v e r y e x p e n s i v e t o o b t a i n . The c o s t o f d e t e r m i n i n g a c r y s t a l s t r u c t u r e has d e c l i n e d g r e a t l y i n t h e p a s t few y e a r s ; and t h e l i t e r a t u r e abounds w i t h u s e f u l c r y s t a l s t r u c t u r e r e s u l t s . W i t h the proper computer f a c i l i t i e s , m o l e c u l a r mechanics c a l c u l a t i o n s a r e e a s y t o s e t up and r u n . C r y s t a l s t r u c t u r e r e s u l t s c a n be used to p r o v i d e the experimental v e r i f i c a t i o n necessary f o r i n s u r i n g t h a t m o l e c u l a r m e c h a n i c s r e s u l t s have v a l i d i t y i n t h e molecules being c a l c u l a t e d . Special computational techniques c a n be u s e d t o e x p l o r e non-minimum e n e r g y c o n f o r m a t i o n s and t o c o n f o r m a t i o n a l l y m a t c h m o l e c u l e s . The a p p r o a c h can be e x t e n d e d t o a l l o w t h e b u i l d i n g and t e s t i n g o f a model f o r r e c e p t o r requirements provided s t r u c t u r a l i n f o r m a t i o n i s a v a i l a b l e on a number o f m o l e c u l e s w h i c h i n t e r a c t a t t h e r e c e p t o r . Advances i n computer technology a r e r e d u c i n g the c o s t o f c o m p u t e r s and a r e m a k i n g t h i s p r o c e s s l e s s e x p e n s i v e . New, l e s s e x p e n s i v e and f u n c t i o n a l l y improved i n t e r a c t i v e g r a p h i c s terminals are being introduced, i n c l u d i n g terminals with f a i r l y h i g h r e s o l u t i o n c o l o r g r a p h i c s . The t r e n d toward l e s s e x p e n s i v e c o m p u t i n g and g r a p h i c s w i l l r e d u c e t h e c o s t o f t h i s q u a n t i t a t i v e model b u i l d i n g t e c h n i q u e t o t h e p o i n t t h a t a l l m e d i c i n a l c h e m i s t s c a n have e a s y a c c e s s t o s u c h d e v i c e s . Indeed, pharmac e u t i c a l c o m p a n i e s and o t h e r l a r g e r e s e a r c h f a c i l i t i e s w i l l n o t be a b l e t o a f f o r d n o t t o p r o v i d e t h e i r c h e m i s t s w i t h s u c h facilities. J u s t a s with other drug design t o o l s , the study o f t h r e e d i m e n s i o n a l s t r u c t u r e a s d e s c r i b e d i n t h i s p a p e r does n o t g i v e a c o m p l e t e p i c t u r e o f a d r u g m o l e c u l e and i t s a c t i o n s . E l e c t r o n i c e f f e c t s a r e s t u d i e d o n l y i n a p e r i p h e r a l way h e r e ; quantum m e c h a n i c s c a l c u l a t i o n s , a s d e s c r i b e d b y C h r i s t o f f e r s e n i n t h e f i r s t p a p e r o f t h i s symposium, can b e u s e d t o o b t a i n f u r t h e r v a l u a b l e i n f o r m a t i o n . N e i t h e r o f t h e a b o v e , however, g i v e much d i r e c t i n f o r m a t i o n a b o u t t h e t r a n s p o r t o f d r u g s t o t h e s i t e o f a c t i o n . Drug d e s i g n i s a v e r y c o m p l i c a t e d p r o c e s s , n e c e s s i t a t i n g t h e u s e o f a number o f t o o l s , e a c h h a v i n g s t r e n g t h s i n c e r t a i n a r e a s . C r y s t a l s t r u c t u r e a n a l y s i s and m o l e c u l a r m e c h a n i c s o c c u p y a p r o m i n e n t p l a c e among t h e t o o l s o f d r u g design.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

3.

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Molecular Mechanics

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LITERATURE CITED 1.

Duchamp, D . J . and Campbell, J.Α., Acta Cryst., (1972), A28, S50.

2.

Kennard, O. and Watson, D . G . , "Molecular Structures and Dimensions", Volumes 1-9, Crystallographic Data Centre, Cambridge, England (1970-1979).

3.

Duax, W . L . , and Norton, D . A . , "Atlas of Steroid Structure", (1975), New York, IFI/Plenum, (Volume 2, in press).

4.

Shoemaker, D . P . , in: " C r i t i c a l Evaluation of Chemical and Physical Structural Information", Lide, D.R. and Paul, M.A. e d . , Washington, National Academy of Sciences, 1974, p. 157-185.

5.

Ibers,

6.

Donahue, J., ibid., p. 199-218.

7.

Stout, G.H. and Jensen, L.H., "X-ray Structure Determin­ ation", Macmillan, New York (1968).

8.

Duchamp, D.J., Chidester, C.G., Olson, E.C., Amer. Cryst. Assoc. Abstr. Papers (summer meeting), (1977), 5, 83.

9.

Kitaigorodsky, A.I., "Molecular Crystals and Molecules", Chapter V I I , Academic Press, New York (1973).

10.

Engler, E.M., Andose, J.D., and von Schleyer, R.P., JACS, (1973), 95, 8005.

11.

Schroeder, R. and Lippincott, E.R., J. Phys. Chem. (1957), 61, 921.

12.

Duchamp, D.J., Cheney, B.V., unpublished work.

13.

Duchamp, D.J., in: "Algorithms for Chemical Computations", Christoffersen, R . , ed. Washington: ACS, 1977, p. 98-121.

14.

For peptide amide parameters, see, for example, Marsh, R . E . and Donohue, J., Adv. Protein Chem. (1967), 22, 235.

15.

Moelwyn-Hughes, E.A., "Physical Chemistry", 2nd Revised E d i t i o n , Pergamon Press, New York, (1961), p. 518-519.

16.

Williams, D.E., Acta Cryst., (1974), A30, 71.

J.Α.,

ibid.,

p. 186-198.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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17.

Ermer, O. and L i f s o n , S . , JACS, (1973), 95, 4121.

18.

Govers, H.A.J., Acta Cryst., (1975), A31, 380.

19.

Bates, J . R . and Busing, W.R., J. Chem. Phys., (1974), 60, 2414.

20.

Momany, F.A., Carruthers, L.M., McGuire, R.F., and Scheraga, H . A . , J. Phys. Chem., (1974), 78, 1595. (And previous papers from H.A. Scheraga.)

21.

A l l i n g e r , N . L . and Sprague, J.T., JACS, (1973), 95, 3893. (and previous papers from N . L . Allinger).

22.

Williams, D.E., Trans. Amer. Cryst. Assoc., (1970), 6, 21.

23.

Stenkamp, R . E . and Jensen, L.H., Acta Cryst., (1973), B29, 2872.

24.

Cheney, B.V., Duchamp, D.J., and Christoffersen, R.E., i n : "Quantitative Structure Activity Relationships of Analgesics, Narcotic Antagonists, and Hallucinogens", Barnett, G., Trsic, Μ., and Willett, R.E., ed., NIDA Research Monograph 22, Washington, (1978), p. 218-249.

25.

Von Koningsveld, H., Rec. Trav. Chim., (1970), 89, 375.

26.

Beckett, A. and Casey, Α., Prog. Med. Chem., (1965), 4, 171.

RECEIVED June 29,

1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

4 Studies of Chemical Structure-Biological Activity Relations Using Pattern Recognition 1

P. C. JURS, J. T. CHOU, and M. YUAN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch004

Department of Chemistry, 152 Davey Laboratory, The Pennsylvania State University, University Park, PA 16802

The attempt to rationalize the connection between the molecular structures of organic compounds and their biological activities comprises the field of structure-activity relations (SAR) studies. Correlations between structure and activity are important for the development of pharmacological agents, herbicides, pesticides, and chemical communicants (olfactory and gustatory stimulants) and for the investigation of chemical toxicity and mutagenic and carcinogenic potential. Practical importance attaches to these studies because the results can be used to predict the activity of untested compounds. In addition SAR studies can direct the researcher's attention to molecular features that correlate highly with biological activity, thus confirming or suggesting mechanisms or further experiments. SAR studies have been used to some extent in the pharmaceutical and agricultural industries. The methods are beginning to be applied to the important problems of chemical toxicity and chemical mutagenesis and carcinogenesis. The superior way to develop predictive capability is to understand, at the molecular level, the mechanisms that lead to the biological activity of interest. Unfortunately, this knowledge is not yet available for most classes of biologically active compounds. Furthermore, the progress made through a living system by an active compound or its precursors is not usually known. Thus, two choices are presented: study the mechanisms for a very few compounds to develop fundamental information for those few compounds, or use empirical methods to study larger sets of compounds with correlative methods. The latter method comprises an SAR approach to the problem. Thus, one has available a set of compounds that have been tested in a standard bioassay and the observations that resulted from the tests. One can then search for correlations between the structures of the compounds tested and the biological observations reported. One is actually 1

Current address: Stauffer Chemical Co., 1200 S. 47th Street, Richmond, CA 94804. 0-8412-0521-3/79/47-112-103$06.75/0 © 1979 American Chemical Society In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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modelling the entire process of uptake, transport, distribution, metabolism, c e l l penetration, binding, excretion, etc. The discovery and design of biologically active compounds (drug design) i s a f i e l d that has been subject to widespread and well-documented ÇL-j8) changes i n the past decade. A host of new techniques and perspectives have evolved. While these techniques have been used largely for the development of pharmaceuticals, they can also be applied to the rationalization of structureactivity relations among sets of toxic, mutagenic, or carcinogenic compounds. Several approaches to SAR have been reported: the semiempirical linear free energy (LFER) or ext rat hemodynamic model proposed by Hansch and coworkers (9,10,11), the additivity or Free-Wilson model (12); quantum mechanically based models (13,14) and pattern recognition methods (8,15). Reviews are cited that describe the progress made using each of the approaches. Chemical and SAR Applications of Pattern Recognition. Pattern recognition i s a subfield of a r t i f i c i a l intelligence comprise of a set of nonparametric techniques used to study data sets that may not conform to well-characterized probability density functions. A voluminous literature describes the f i e l d (16,17,18,19). Most of the pattern recognition methods share a set of common properties. The data to be analyzed, here molecular structures of carcinogens and noncarcinogens of interest, are represented by points i n a high dimensional space. For a given compound, which i s represented by a given point, the value of each coordinate i s just the numerical value for one of the molecular structure descriptors comprising the representation. The expectation i s that the points representing carcinogenic compounds w i l l cluster i n one limited region of the space, while the points representing the noncarcinogenic compounds w i l l cluster elsewhere. Pattern recognition consists of a set of methods for investigating data represented i n this manner to assess the degree of clustering and general structure of the data space. Parametric methods of pattern recognition attempt to find c l a s s i f i c a t i o n surfaces or clustering definitions based on s t a t i s t i c a l properties of the members of one or both classes of points. For example, Bayesian c l a s s i f i c a t i o n surfaces are developed using the mean vectors for the members of the classes and the covariance matrices for the classes. If the s t a t i s t i c a l properties cannot be calculated or estimated, then nonparametric methods are used. Nonparametric methods attempt to find clustering definitions or c l a s s i f i c a t i o n surfaces by using the data themselves directly, without computing mean vectors, convariance matrices, etc. Examples of nonparametric methods would include error-correction feedback linear learning machines (threshold logic units or perceptrons) and simplex optimization methods of searching for separating c l a s s i f i c a t i o n surfaces. Complete descriptions of these methods can be found i n standard texts (19).

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Applications of pattern recognition methodology to chemical problems were f i r s t reported in the I960 s (20,21) with studies of mass spectra. Since then papers have described work in a variety of areas (22,23) including mass spectrometry, infrared spectroscopy, NMR spectroscopy, electrochemistry, materials science and mixture analysis, and the modeling of chemical experi­ ments. Diagnosis of pathological conditions from sets of measure­ ments made on complex biological mixtures, e.g., serum, have been reported (24). The successes i n these areas have led to the belief that these methods should prove useful i n the development of structure-activity relations. A number of studies of the application of pattern recognition to the problem of searching for correlations between molecular structure and biological a c t i v i t y have been reported. A large fraction of the effort in this area must be devoted to the generation of appropriate descriptors from the molecular struc­ tures available. Areas of study include drug structure-activity relations, studies of chemical communicants, etc. Applications of pattern recognition to drug design have been reviewed by Kirschner and Kowalski (15). Recently, papers have begun to appear reporting the appli­ cations of SAR methods to sets of chemical carcinogens. One study reports correlations between the number of carbon atoms per compound and carcinogenic activity for a set of forty-seven carcinogenic nitrosamines (25). Correlations of carcinogenic activity and l i p o s o l u b i l i t y for small sets of cyclic nitrosamines have been reported (26). Carcinogenic activity was correlated with the theoretical reactivity indices for twenty-five repre­ sentative polycyclic aromatic hydrocarbons (27). A quantitative relationship was reported that correlated carcinogenic activity with the hydrophobic parameter π and the Taft polar substituent constant for twenty-one nitrosamines (28). Correlations were reported between nitrosamine carcinogenic activity and molecular connectivity indices (29). Another study of cyclic nitrosamines found correlations between carcinogenic potency and aqueous and octanol solvation free energies (30). A paper has appeared describing the application of the SIMCA method of pattern recog­ nition to the SAR study of 4-nitroquinoline 1-oxides (31). Hansch and Fujita derived an equation relating the logarithm of carcinogenicity of 47 polycyclic aromatic hydrocarbons with the logarithm of the 1-octanol/water partition coefficient, the total charge of the K-region (32). Franke correlated carcinogenic a c t i v i t y , characterized by the hydrophobic binding pf PAH s to human serum albumin, to a chemical reactivity index for 34 com­ pounds (33). Jurs and coworkers used pattern recognition methods to study a set of 209 diverse chemical carcinogens (34).

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1

1

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Experimental The SAR studies reported here were done using the ADAPT computer software system (35,36). ADAPT has been implemented on the Department of Chemistry MODCOMP 11/25 16-bit d i g i t a l computer in FORTRAN. The fundamental steps involved i n performing an SAR study using this system are shown i n Figure 1. The individual steps are implemented in a series of independent programs that can be executed individually. They perform the mutually supportive tasks necessary for an SAR study as follows: (1) Entry and storage of molecular structures and substructures. (2) Entry and storage of a l i s t comprising those structures to be considered as the current data set of interest. (3) Generation of three dimensional molecular models of the structures using molecular mechanics. (4) Generation and storage of molecular structure descriptors from the topological or geometrical representations of the structures. (5) Gathering together of a common set of descriptors for each compound under investigation to prepare a data set for pattern recognition analysis. (6) Analysis of the data for correlation, separability, etc. using techniques drawn from s t a t i s t i c s , nonparametric s t a t i s t i c s , and pattern recognition. Testing of discriminants for predictive ability. (7) Identification of which of the currently active descriptors are contributing to solution of the problem and which are unimportant enough to discard; that i s , feature selection. Each of these tasks w i l l be discussed i n more detail i n the following paragraphs. Entry of Structures and Substructures. The main data input to the ADAPT system i s chemical structures along with the relevant biological or physicochemical property. Structures are entered by sketching on the CRT screen of a graphics display terminal. The information contained i n the sketch i s converted into a compressed connection table representing the atom types, the bond types, and the bonding pattern, i . e . , the topology. Rings are automatically perceived and labelled. The user supplies pertinent stereochemical information during sketching. A l l the topological information, along with additional information such as the name of the compound, associated numerical information, etc. are saved on ADAPT disc f i l e s cataloged under an accession number for each compound. Routines allow the retrieval for review of any structure, the deletion of any structures, the alteration of any structure. The system i s configured on the MODCOMP 11/25 so that one cartridge disc w i l l hold one thousand structures i n addition to a l l other ADAPT disc f i l e s for other storage.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch004

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ENTRY ON connection STORAGE OF ^ tables ^ MOLECULAR * • STRUCTURES

d

DESCRIPTOR GENERATION

a

t

s e t

*

a

PATTERN RECOGNITION * ANALYSIS

A

3-DIMENSIONAL MODEL BUILDING

Figure 1. Flow chart of steps involved in structure-activity studies using chemical structure information handling and pattern recognition techniques

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Substructures are entered into the system using the same procedures, but they are stored on special, separate disc f i l e s . They are used by the substructure searching routine during descriptor generation.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch004

Entry and Storage of List of Structures for Study. The ADAPT disc f i l e s can store more structures than can be studied at once, so each SAR study must have i t s own l i s t of structures of interest. This l i s t i s called the worklist. It comprises the set of structures for which descriptors are to be generated and stored. Molecular Mechanics Model Building. A three-dimensional molecular model builder routine interfaced to the ADAPT system (MOLMEC) i s used to derive information on the spacial conforma­ tion of molecules. The molecules are viewed as collections of particles held together by simple harmonic or elastic forces. A strain energy can be defined for a molecule which i s the sum of contributions for each of several items: Ε _

.

strain =

Ε , ,

Dond

+ Ε

,+E angle

. +E , J + torsion nonbond

E

_

stereo

The f i r s t four terms of the function are commonly found i n mole­ cular mechanics strain energy functions, and they are modified Hooke's law functions. The last term has been added to insure the proper stereochemistry about asymmetric atoms. A model i s refined by minimizing the highly nonlinear strain energy function with respect to the atomic coordinates. An adaptive pattern search routine i s used for the strain energy minimization because i t does not require analytical derivatives. The time necessary to obtain good molecular models depends on the number of atoms in the molecule, the f l e x i b i l i t y of the structure, and the quality of the starting model. The molecular mechanics routine i s highly interactive and relies on graphical input and output. A molecule being modelled can be displayed in any desired orientation for inspection by the user. If such inspection shows that the model i s trapped in a local minimum of the strain energy, then interactive routines allow the user to alter the model to bring i t out of the minimum. An automatic version of MOLMEC has been implemented so that large sets of molecules can be modelled without continuous super­ vision. The routine i s set up so that i t can u t i l i z e computer time that would otherwise go unused, and so that i t can be inter­ rupted and restarted in order to allow modelling to continue for long periods. The purpose of the molecular modelling i s to generate models of sufficient quality to allow the computation of geometric descriptors, allow r e a l i s t i c perspective drawings of molecular

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structures, and to provide geometries for input to molecular orbital calculations. Descriptor Generation. Topological descriptors are generated from the connection tables of the structures. Each descriptor development routine i s independent, fetching the structures of the compounds being coded from the disc f i l e s , generating the particular descriptor, and storing the results on other disc files. Fragment Descriptors: Fragment descriptors include the atom type counts, bond type counts, the molecular weight of the compound, the number of ring atoms, and the number of basis rings in the compound. These simple descriptors provide fundamental information regarding the structures being represented. Substructure Descriptors: This routine generates descriptors using a generalized substructure search algorithm. The substructure (s) to be searched are entered into the substructure storage area using the sketching input described above. Their accession numbers are supplied to the substructure descriptor routine by the user at execution time. The descriptor value for a compound i s the number of times the substructure i s found imbedded within that structure. A variety of options may be invoked by the user, such as requiring ring atoms to match ring atoms, using relaxed c r i t e r i a of connectivity for matching, or finding a l l substructure occurrences or only unique, nonoverlapping occurrences. Molecular Connectivity Descriptors: The molecular connectivity index of a molecule i s a measure of the branching of the structure. The path one molecular connectivity index i s formed by summing contributions for each bond i n the structure, where the contribution for each bond i s determined by the connectivity of the atoms that are joined by that bond. Higher order molecular connectivities can also be computed by considering a l l paths of length two, three, etc. These descriptors have been shown in several published reports to be correlated with a number of physicochemical parameters, such as partition coefficients and steric parameters (37,38,39). Environment Descriptors: The immediate surroundings of a substructure, as i t i s imbedded within a structure, i s coded by the environment descriptor. Once a substructure i s found within the structure being coded, then a pseudomolecule is formed from the substructure match atoms of the structure and their nearest neighbor atoms. Then a path one molecular connectivity calculation i s done over this pseudomolecule to form the environment descriptor. Thus, a value i s obtained that indicates not only the presence of the substructure, but also i t s surroundings in the molecule. Path and Path Environment Descriptors: Molecular structures can be viewed in the abstract as graphs, in the mathematical sense. Graphs have a number of properties that can be readily

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computed, among them paths. A path i s a sequence of connected atoms in which no atom appears more than once. The tracing of paths i n highly connected graphs, e.g., polycyclic aromatic hydrocarbons, i s tedious but can be done. A method for finding a l l the paths contained i n a graph has been published, with a discussion of the chemical u t i l i t y of this measure of bonding complexity (40). A descriptor generation routine has been implemented and interfaced to ADAPT using this concept. The routine calculates the total number of paths of a l l lengths contained within the structure being coded. The path environment descriptor i s similar to the molecular connectivity environment descriptor. A substructure i s matched against the structure being coded. If i t i s present, then a pseudomolecule i s formed from the substructure atoms and their f i r s t nearest neighbor atoms. Then the number of paths o r i g i nating from the set of atoms forming the pseudomolecule i s found. The maximum path length to be considered i s input by the user. The descriptor for a particular structure consists of the number of paths originating from the substructure atoms and their f i r s t nearest neighbors. This environment descriptor can be made sensitive to the immediate surroundings of the substructure by making the maximum path length to be considered very small, e.g., two or three. Alternatively, i t can be made sensitive to the overall structure of the molecule by making the maximum path length larger. Sigma Charge Calculation: As a f i r s t attempt to provide the system with an electronic descriptor, a sigma charge calculation routine has been implemented following the discussion of the Del Re method by Hopfinger (41). The Del Re method (42) i s a simple calculation whereby bond charges are calculated i n a Huckel formalism and are summed about each atom to give the total sigma charge for each atom. Each bond orbital i s described as a linear combination of atomic orbitals. This sigma charge calculation program has been interfaced with the substructure searching routine to develop the sigma charge descriptor. The routine searches for a specified substructure i n a molecule, and, i f present, the sigma charge calculation i s done for the entire molecule. The descriptor i s then generated i n one of two ways. In order to investigate the sigma charge of a particular region of a set of molecules, the descriptor can be the average sigma charge of the atoms comprising the substructure used for searching. If the substructure occurs more than once within the structure, the descriptor value i s the average sigma charge over a l l occurrences of the substructure. In i t s alternate forms the descriptor can code the sigma charge on the most positive atom within the substructure or the sigma charge on a specified substructure atom. In the event that the Del Re sigma charge parameters are not available for a particular bond i n the molecule under consideration, or, i f the molecule under consideration i s too large for

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the program to handle, the weighted average of the active and nonactive classes i s assigned to that particular compound and the user i s notified by a message. A specific example w i l l c l a r i f y the procedure. When the sigma charge descriptor i s generated using the following substructure with four differently substituted 12-methyl benz(a)anthracenes, the differences i n electron withdrawing power of the 7 position substituents are reflected i n the descriptor value. The dashed lines represent aromatic bonds, and the terminal X's represent atoms of indetermined type and indéterminé connectivity.

CH^

X ι I I

I X

The four compounds and their average sigma charges on the sub­ structure are as follows: (a) 7,12-dimethylbenz(a)anthracene 0.00433; (b) 7-formyl-12-methylbenz(a)anthracene 0.00604; (c) 7cyano-12-methylbenz(a)anthracene 0.0176; and (d) 7-fluoro-12methylbenz(a)anthracene 0.0754. Despite the fact that this semi-empirical technique deals only with the sigma electron contribution and was developed for the study of saturated organic molecules, the descriptors deve­ loped by the routine have found u t i l i t y i n the study of poly­ cyclic aromatic hydrocarbons, as w i l l be shown. Partition Coefficient Estimation: The log P, the logarithm and a model l i p i d phase, i s highly correlated with various types of biological a c t i v i t i e s . Its inclusion as a descriptor allows the system to have access to information regarding transport and partitioning that may not be as clearly represented i n the other descriptors. The calculation of log Ρ can be done using a "constructionist approach" due to Leo, Hansch and coworkers (43, 44). This formulation starts with a set of fundamental fragments whose values are summed with appropriate weightings. Corrections are added to refine the calculation i f necessary. The equation used i s as follows: η log Ρ = Σ * i i i=l f

+

m Σ j j-1 c

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where f± i s the fragment constant for the i t h fragment, a-^ i s the number of occurrences of the i t h fragment, and C J i s the j t h correction factor. The fundamental assumption of this approach i s that hydrophobicity i s an additive-constitutive property of mole­ cules. Recently, this fragment constant method has been implemented in a routine and interfaced to ADAPT (45,46). Thus, the estimated log Ρ value for a molecule can be used as a descriptor along with a l l the other descriptor types. Geometric Descriptors: Once the set of molecules being studied have been modelled, then descriptors can be generated from these models. Geometrical descriptors that have been used i n many structure-activity studies are the three principal moments of inertia of the molecules, the three ratios of these three p r i n c i ­ pal moments, and the molecular volume. Many other geometrical descriptors can be envisioned, and the development of new descrip­ tors i s an area of active interest. Descriptor Manipulation Routines: In addition to the individual descriptor generation routine, the ADAPT system contains several support routines. There i s a general maintenance and interrogation routine for the descriptor f i l e s that allows the user to review descriptor values by l i s t i n g them, to delete unwanted descriptors, etc. Another routine allows the user to input descriptors obtained from any source from cards so that they can be studied along with the computer generated descriptors. A manipulation routine allows the user to alter previously gener­ ated or stored descriptors to form new descriptors. Addition, subtraction, multiplication, division, exponentiation, logarithmic transformation, autoscaling, inversion, etc. are allowed. Gathering of Common Set of Descriptors. The descriptor f i l e s of ADAPT typically hold many more descriptors for a set of com­ pounds of interest than can be studied at one time. Therefore, a routine allows the user to select which of the available descriptors to form into a data set for analysis. This allows the user to conveniently study different sets of descriptors for the same set of compounds. When a data set i s generated, the descrip­ tors are automatically autoscaled i n order to give each descriptor equal weight i n the subsequent analysis. Pattern Recognition Analysis. A set of interactive pattern recognition programs have been interfaced to the ADAPT system. The same data set can be studed using a variety of techniques for comparative purposes. The analysis routines are a l l interactive. The set of transformed, scaled, and normalized data for the ith compound i s expressed as a pattern vector of the form: x

(x^,X2» ···, χ^, ···9 > n

X

n+1

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where η i s the number of descriptors per compound. The (n+l)th component of the pattern vector i s a constant added for computa­ tional convenience. The set of observations belong to two classes, and the fundamental purpose of each of the analysis routines i s to find a discriminant that w i l l separate the two classes. For linear discriminants this i s equivalent to searching for a weight vector, W, such that the dot product of with W

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s. = W · X

±

w i l l be positive for a l l members of one class and negative for a l l members of the other class. Logically, the analysis part of the ADAPT system breaks down into several subsections: u t i l i t y routines, parametric pattern recognition methods, nonparametric pattern recognition methods, and feature selection routines. Each i s discussed i n the follow­ ing paragraphs. A training set/prediction set generation routine allows the user to enter into disc f i l e s l i s t s of which patterns i n the current data set are to comprise a training set and which patterns are to comprise a prediction set. A number of options exist whereby the user can generate training set/prediction set combin­ ations using random selection of members of the data set, random selection with some of the patterns excluded from consideration, training sets consisting of a l l the patterns but k where k i s a user supplied number, etc. The system i s configured to be able to store up to 100 training set/prediction set combinations. The resulting l i s t s of training set members and prediction set members are accessed by the pattern recognition routines i f directed to do so. A weight vector u t i l i t y routine allows the user to enter a weight vector into the appropriate disc storage area so that i t can be used to i n i t i a l i z e any of that pattern recognition programs. The routine can also output any stored weight vector. Any of the linear discriminant development routines can store a trained weight vector i n the same weight vector storage area. Thus, the weight vector resulting from execution of one pattern recognition program can be used to i n i t i a l i z e another of the programs. This feature has proved to be very useful i n many studies. Parametric Pattern Recognition Programs: The parametric pattern recognition programs use the mean vectors and covariance matricies (or other saturated measures) of the two classes into which the patterns f a l l as their basis for development of dis­ criminants . One parametric routine implements a quadratic discriminant function using the Bayesian theorem. The equation for the discriminants are as follows: d (X) k

= In p

- è In |c | - è [(X-m ) C ^ T

k

k

k

1

(X-m^.) ] k=l,2

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where p^ i s the a_ p r i o r i probability for class k, Cfc i s the covariance matrix for class k, and 1% i s the mean vector for class k (19). This discriminant assumes a multivariate normal distribution of the data. A pattern, X± i s put in the class for which dfc(Xi) i s greatest. If the assumption i s made that the covariance matrices for the two classes are the same, then the discriminant function developed using the Bayes theorem and the multivariate normal assumption simplifies from that above to the following: 9

s = d (X)-d (X) = In p Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch004

1

2

- è m^'C

x

- In p

"Sn^ + i n^'C

2

+

1

X'x" ^^)

m

^2

where s i s greater than zero for one class and less than zero for the other class. This routine implements this linear discriminant function. The covariance matrix, C, can be calculated using the members of either of the two classes of patterns or using the entire training set, at the user's option. Another parametric routine implements a discriminant function by the method commonly called linear discriminant function analysis. It i s nearly identical to the linear Bayesian discriminant, except that instead of using the covariance matrix, the sum of cross-products matrix i s used. Results obtained with the routine are ordinarily very similar to those obtained using the linear Bayes routine. The routine implemented as LDFA i s a highly modified version of program BMD04M taken from the Biomedical Computer Programs Package (47). Nonparametric Pattern Recognition Programs: The nonparametric pattern recognition programs develop their discriminants using the training set of patterns to be classified rather than s t a t i s t i c a l measures of their distributions. The k nearest neighbor routine i s conceptually the simplest. An unknown pattern i s assigned to the class to which the majority of i t s nearest neighbors belong. The metric that i s used to determine proximity i s ordinarily the Euclidean metric, but any metric can be used. The system contains a routine that implements the familiar linear learning machine or perceptron (19,22). The algorithm i s heuristic. A decision surface i s i n i t i a l i z e d either a r b i t r a r i l y or i s input from a disc f i l e that was previously f i l l e d using the weight vector u t i l i t y routine or one of the other linear discriminant development routines. Then the learning machine classifies one member of the training set at a time. When the current discriminant function correctly c l a s s i f i e s a pattern, the discriminant i s l e f t unchanged. However, whenever an incorrect c l a s s i f i c a t i o n i s made, then the discriminant i s altered in such a way that the error just committed i s eliminated. The learning

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machine continues to classify the members of the training set repeatedly u n t i l no errors are committed or u n t i l the user termi­ nates the routine. This algorithm for development of linear discriminant functions has the desirable property that i f a training set of patterns i s separable into the two classes, i.e.; i f a solution exists, then this method w i l l find a solution. This routine i s the one ordinarily used to train a set of slightly different weight vectors to be used for the variance method of nonparametric feature selection. Another nonparametric routine develops a linear discriminant function through an iterative least squares approach (22). The function i s minimized: m γ

2

Q = Σ [ ι " F( )] i=l where m i s the total number of patterns in the training set, Y^ equals +1 for one pattern class and -1 for the other class, s^ i s the dot product of the weight vector with the i t h pattern vector, and F(si) i s the hyperbolic tangent function of s i . The hyperbolic tangent function has the values of positive one for a l l positive values of s± and negative one for a l l negative values of s^. Therefore, minimizing Q i s equivalent to minimizing the number of incorrect classifications. The function i s non­ linear i n the independent variables and thus can not be solved directly, so an iterative algorithm i s employed. This routine has been found to be particularly useful for dealing with data that are not separable into the two classes. A linear discriminant function can be found using a linear programming approach (48,49). The objective function to be optimized consists of the fraction of the training set correctly c l a s s i f i e d . If two vertices have the same c l a s s i f i c a t i o n a b i l i t y , then the vertex with the smaller sum of distances to misclassified points i s taken as better. Another routine develops a decision tree of binary choices which, taken as a whole, can classify the members of the training set. The decision tree generated implements a piecewise linear discriminant function. The decision tree i s developed by s p l i t t i n g the data set into two parts in an optimal way at each node. A node i s considered to be terminal when no advantageous s p l i t can be made; a terminal node i s labelled to associate with the pattern class most represented among the patterns present at the node. S i

Feature Selection. Once a data set has been established to be linearly separable, then variance feature selection (50) can be used to discard the least useful descriptors and thereby focus on the more useful descriptors. Several routines are implemented

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in ADAPT to allow the application of variance feature selection to a data set i n a convenient, interactive way. Polycyclic Aromatic Hydrocarbon Study (51). The data were •taken from papers by Dipple (52) and McCann et a l . (53). In the Dipple data set, several hundred polycyclic aromatic hydrocarbons are arranged according to their carcinogenic potency into four classes: inactive, slight, moderate, and high. These classifications are based upon the percentage of treated animals which developed tumors when exposed to the compounds. Slight carcinogens are those compounds which caused tumors in up to 33% of the test animals. Moderate carcinogens are those compounds which caused tumors i n between 33% and 66% of the test animals. High carcinogens are those compounds which caused tumors i n 66% or more of the test animals. In the McCann data set, 209 compounds in ten different classes (e.g., aromatic amines, N-nitroamines, polycyclic aromatic hydrocarbons) are compiled. From this group of compounds a number of polycyclic aromatic hydrocarbons not already present i n the Dipple data set were selected. These compounds were only classified as carcinogens or noncarcinogens. In most cases, these compounds were tested i n either mice or rats, by subcutaneous injection, giving rise to sarcomas, or by application to the skin, giving rise to benign papillomas or malignant eptheliomas. In the Dipple data set, i n some cases, compounds were c l a s s i fied into several categories because different results were obtained with different species or with different models. For example, 5-methyl Benz(a)anthracene i s classified as an inactive compound when i t i s injected intramuscularly into rats. It i s classified as a slight carcinogen when i t i s either painted on mouse skin, or subcutaneously injected into rats. Finally, i t i s c l a s s i f i e d as a moderate carcinogen when i t i s subcutaneously injected into mice. Because most of the pattern recognition algorithms used i n this study are binary pattern c l a s s i f i e r s , the four categories used by Dipple were reduced to two, namely carcinogens and noncarcinogens. A compound was classified as a noncarcinogen i f and only i f i t was classified by Dipple as either inactive or inactive and slight. A compound was c l a s s i f i e d as a carcinogen i f and only i f i t was classified by Dipple as either high, moderate, high and moderate, high and slight, moderate and slight, or high and moderate and slight. A set of 200 PAH compounds were randomly selected from those stored for study. They f a l l into sixteen structural classes as shown i n Table I. There are 73 carcinogens and 127 noncarcinogens i n the set. Each compound was modelled to obtain a three dimensional geometry for use i n geometrical descriptor development. For each of the 200 compounds more than 50 descriptors were generated. The 28 descriptors f i n a l l y found to be the best set are shown in

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TABLE I.

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CHARACTERIZATION OF THE 200 COMPOUND PAH DATA SET

Carcinogens Anthracenes Benz(a)acridines Benz(c)acridines Benz(a)anthracenes Benz(c)phenanthrenes Benzο(a)pyrenes Carbazoles Cholanthrene s Chrysenes Cyclopenta(a)phenanthrenes Dibenz(a,h)anthracenes Miscellaneous Heterocycles Miscellaneous PAH Phenanthrenes Pyrenes Triphenylenes Totals

Noncarcinogens

2 0 3 23 0 13 5 5 0 2 4 6 10 0 0 0

10 17 10 41 4 5 0 5 3 14 1 0 10 3 2 2

73

127

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Table II. The substructures used for the generation of the environment descriptors and the sigma charge descriptors are shown i n Figure 2. In this figure a terminal X indicates an atom of undetermined type and undetermined connectivity. An X found imbedded i n a substructure, such as the X found i n substructure 4, is constrained to have the connectivity found i n the substructure to obtain a match, but any atom type. For example, the substituent on the benzo ring i s substructure 5 can be a methyl group, a chlorine, or an ethyl group, among others. The mean and standard deviation for each descriptor and the values for 7,12dimethyl benz(a)anthracene are shown in Table III. This set of 28 descriptors supported linear discriminants that could completely separate 191 of the PAH s into the active and inactive classes. This i s a recognition rate of 95.5 percent. There are 66 carcinogens and 125 noncarcinogens i n this set of compounds. Predictive a b i l i t y tests were performed with the 28 descriptors. In a series of randomized t r i a l s 400 predictions were performed. Actual carcinogens were predicted with 87.5 percent accuracy and noncarcinogens with 92.5 percent accuracy for an average of 90.5 percent. These results show that pattern recognition can be used as an effective tool to characterize polycyclic aromatic hydrocarbon carcinogens. Using a set of only 28 molecular structure descriptors, linear discriminants can be found to correctly dichotomize 191 out of 200 randomly selected PAH's. This same set of 28 descriptors supports a linear discriminant function that has an average predictive a b i l i t y of over ninety percent when subjected to randomized predictive a b i l i t y tests. The 28 descriptors selected i n this study are a notably diverse set. A l l types of descriptors available have been found useful in the analysis. One can interpret this selection of such a diverse set of descriptors as an indication that PAH carcinogenesis i s a complex process involving many factors, and that one might expect the most success at developing structure-activity relationships with a multifaceted approach to the problem. Among the descriptors chosen i s the logarithm of the calculated 1-octanol/water partition coefficient, indicative of the important influence of transport properties. Substructural descriptors, involving both connectivity environment calculations and average sigma charge calculations are perhaps indicative of particular regions of the molecules that might be involved in PAH carcinogenesis. Both bay-region substructures and K-region substructures were retained after feature selection. The influence of overall molecular size i s well represented by several geometric descriptors, the fragment descriptor representing the number of rings in the compound, and the descriptor representing the square of the area of the molecule. Of particular interest are the geometrical descriptors and other descriptors representing some aspect of molecular size or 1

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch004

DESIGN

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TABLE I I . TWENTY-EIGHT DESCRIPTORS USED FOR PAH STUDY

Descriptor The number of oxygen atoms The number of fluorine atoms The number of double bonds The number of rings The molecular volume Path 1 molecular connectivity, using heteratom valences, ring corrected 7. Path 2 molecular connectivity 8. The X principal radius 9. The Ζ principal radius 10. The X principal radius/ The Y principal radius 11. The X principal radius/ The Ζ principal radius 12. The Y principal radius/ The Ζ principal radius 13. The molecular connectivity of substructure 1 14. The mole, connect, of substr. 2 15. (X prin. radius χ Y prin. radius)^ 16. The mole, connect, of substr. 3 17. The mole, connect, of substr. 4 18. The mole, connect, of substr. 5 19. The mole, connect, of substr. 6 20. The mole, connect, of substr. 7 21. The mole, connect, of substr. 8 22. The logarithm of the 1-octanol/water partition coefficient 23. The average sigma charge of substructure 9 24. The average sigma charge of substructure 1 25. The average sigma charge of substructure 8 26. The average sigma charge of substructure 10 27. The average sigma charge of substructure 6 28. The average sigma charge of substructure 5

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1. 2. 3. 4. 5. 6.

Note:

The Number of Non-Zero Occurrences 52 14 31 200 200 200 200 200 200 200 200 200 164 26 200 102 17 44 51 16 26 196 19 164 26 66 51 44

Substructures are numbered according to Figure 2.

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X

X

}

}

f

DESIGN

X

ί

1

I

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Τ X

!

A

' V

Y ι ι

.'X

J . ι ^

! Y

*x

-1

r

χ-

"χ

X

X I

Λ

X. Y

I

r

^

x ^ >

X

τ

r

I X

X

'

Ϊ

X

8

Figure 2. The substructures used for calculation of the environment and sigma charge descriptors for the PAH study

10

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TABLE III.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch004

DESCRIPTOR STATISTICS AND SAMPLE DESCRIPTOR VALUES

Descriptor

Mean

Standard Deviation

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28.

0.365 0.080 0.190 4.390 165.950 6.044 5.432 8.832 0.072 3.787 653.340 504.960 3.652 0.638 585.420 2.633 0.440 0.910 1.618 0.506 0.592 6.360 0.000556 0.012536 0.001902 -0.009188 0.000006 -0.001157

0.703 0.323 0.485 0.735 20.677 0.802 0.693 2.344 0.258 1.719 403.620 435.070 1.748 1.655 547.861 2.600 1.451 1.726 2.777 1.724 1.542 1.448 0.002205 0.015061 0.009210 0.017044 0.001883 0.005645

Value for 7,12-Dimethyl Benz(a)anthracene 0 0 0 4 159.001 5.721 5.106 7.285 0.012 3.185 604.796 189.889 4.486 0 277.588 5.251 0 0 0 0 0 6.940 0.003* 0.004' 0 0 0 0

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shape. Of the 28 descriptors surviving feature selection there are five of the six geometrical descriptors generated involving principal r a d i i , the molecular volume descriptor, the fragment descriptor representing the number of rings in the compound, and the descriptor related to the area of the planar or near planar polycyclic aromatic hydrocarbons. The abundance of descriptors which relate size of the hydrocarbons to carcinogenic activity supports arguments made by Arcos (54,55) relating carcinogenic activity to the incumbrance area of the polycyclic aromatic hydrocarbon. The incumbrance area i s the area of the smallest rectangle that can encompass the molecule's van der Waals envelope (54). Their conclusion was that molecules with too great an incumbrance area would be too large to f i t in a receptor site or too large to intercalate into DNA. Those molecules possessing too small an incumbrance area would be bound too loosely to the c r i t i c a l cellular constituent. This size c r i t e r i a has been supported by other studies involving DNA-hydrocarbon binding (54). The importance of molecular size has also been emphasized by Hansch and Fujita (32). However, he suggested that the small hydrocarbons were too hydrophilic and were excreted from the body before they could cause damage. The large hydrocarbons were thought to be insufficiently hydrophilic and easily isolated from c r i t i c a l cellular sites by a small aqueous barrier. Support for the size c r i t e r i a i n this study i s given not only by the fact that a large proportion of the geometric descriptors were retained after feature selection, but also the single most powerful descriptor was the fragment descriptor representing the number of rings in the compound. While the molecular size c r i t e r i a i s no doubt important, the carcinogens cannot be discriminated from the noncarcinogens on the basis of size alone. This, again, suggests that polycyclic aromatic hydrocarbons carcinogenesis i s a complex process involving many different factors, with molecular size being just one of perhaps many important factors. N-Nitroso Compound Study (56). The data used were taken from several sources: Dr. William Lijinksky of the Frederick Cancer Research Center provided most of the data; the remainder came from a published compilation (57) and from papers (53,58). A total of 171 compounds were entered into the ADAPT disc f i l e s . The distribution of the compounds among structural classes i s shown i n Table IV. A subset of the total data set comprising 118 carcinogens (labelled + or w in Table IV) and 35 noncarcinogens (labelled - in Table IV) was used for analysis. For each of the 153 N-nitroso compounds many descriptors were developed and tested. After many t r i a l s of different subsets of descriptors, a f i n a l set of 15 descriptors was selected. This set of 15 descriptors i s shown i n Table V. They provided the best overall performance of the pattern recognition routines of

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TABLE IV.

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DISTRIBUTION OF THE N-NITROSO COMPOUND DATA SET

Number of Compounds

1 w

_1

47 10 3 2 6 3 29 5

6 2 1 1

1

18 7 4 1 3 1 1 0

105

13

35

Structural Class Dialkyl, d i a r y l , or mixed Piperidines Pyrrolidines Morpholines Piperazines Hydraz ine, hydroxylamines Acyl alkyl Misc.

-2

+ : carcinogen w : weak carcinogen - : non-carcinogen ? : controversial or have not been tested

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-1 1 7 —

18

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TABLE V. DESCRIPTORS USED TO REPRESENT 153 COMPOUND N-NITROSO DATA SET

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Index 1 2 3 4 5 6 7 8 9 10 11 12 13

Descriptors Number of Carbon Atoms Number of Nitrogen Atoms Number of Bonds Number of Double Bonds Number of Aromatic Bonds Number of Basis Rings Path 1 Molecular Connectivity (Ring Corrected) Path 1 Molecular Connectivity (Ring and Heteratom Corrected) Path 2 Molecular Connectivity Path 3 Molecular Connectivity Path 4 Molecular Connectivity Environment of Substructure X\ N-N=0 X

14

Average Sigma Charge Substructure

N-N=0 X-X'

15

Average Sigma Charge Substructure

N-N=0 X / where R = -CH , -CH -X, -CH-X, -C-X X X 3

2

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any set of descriptors tested. Included are six fragments, five molecular connectivities, one geometric, one molecular connectiv i t y environment, and two sigma charge descriptors. Table VI provides the means and standard deviations for the 15 descriptors. The f i n a l column of the table shows the descriptor values for 4-methyl-N-nitrosopiperidine:

Among the 153 compounds are included two pairs of diastereoisomers. Because the descriptors cannot distinguish between pairs of diastereoisomers, these four compounds were excluded from further study. In a lengthy series of pattern recognition studies, five additional compounds were identified that had to be excluded from consideration. This leaves a data set of 143 Nnitroso compounds with 116 carcinogens and 28 noncarcinogens. This data set could be completely dichotomized by linear discriminants generated with several different pattern recognition routines. A series of predictive a b i l i t y tests were performed with the 115 descriptors. In a l l , 650 predictions were done. The accuracy of prediction was 91.4 percent overall, 93.4 percent for carcinogens and 84.7 for noncarcinogens. The fact that linear discriminants could be developed to completely separate 116 carcinogenic N-nitroso compounds from 28 noncarcinogenic ones indicates that information concerning the carcinogenic potential of these compounds i s contained i n their structures. A diversity of descriptors are shown to be important in relating structure to carcinogenic potential. Simple fragment descriptors are useful predictors i n this study. Molecular connectivity indices have been shown to be correlated with a variety of biological a c t i v i t i e s (37) including mutagenicity of nitrosamines (29). It has been reported that the partition coefficients of nitrosamines are correlated with their carcinogenicity (25,26). The molecular connectivity indices are also known to be correlated with diverse physico-chemical properties, such as partition coefficients (37). The retention of molecular connectivity descriptors may show this type of relationship. The retention of one shape parameter may indicate the importance of geometry. The electronic properties of nitrosamines have been shown to be related to carcinogenic potential as well (25,59,60, 61). The retention of two sigma charge parameters i n this study supports the hypothesis of the importance of alpha hydroxylation (62,63) i n the bioactivation of nitrosamines.

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TABLE VI.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch004

MEAN AND STANDARD DEVIATIONS FOR THE 15 DESCRIPTORS AND THE DESCRIPTOR VALUES FOR 4-METHYL-N-NITROSOPIPERIDINE

Descriptor Number 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Mean Value 6.28 2.54 10.50 1.63 1.07 0.58 4.21 3.35 2.48 1.54 3.39 2.33 4.09 -0.032 -0.047

Standard Deviation 2.97 0.94 3.46 0.77 2.96 0.67 1.27 1.16 1.01 0.78 2.27 0.40 3.01 0.02 0.05

Value for 4-MethylN-NitrosoPiperidine 6 2 9 1 0 1 2.51 3.00 2.72 1.88 3.14 2.43 6.27 -0.044 -0.044

Acknowledgements This research was sponsored by the National Cancer Institute through contract number N01 CP 75926. The computer used for this work was purchased with p a r t i a l financial support of the National Science Foundation.

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Literature Cited 1. 2. 3. 4.

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5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21.

E.J. Ariens, "Drug Design", Vol. 1-8, Academic Press, New York, 1971-1978. A. Burger, "Medicinal Chemistry", Part I, Wiley-Interscience, New York, 1970. B. Bloom and G.E. Ullyot (Eds.), "Drug Discovery", American Chemical Society, Washington, D.C. 1971. W. Van Valkenburg (Ed.), "Biological Correlations -- The Hansch Approach", American Chemical Society, Washington, D.C. 1972. W.P. Purcell, G.E. Bass, J.M. Clayton, "Strategy of Drug Design", Wiley-Interscience, New York, 1973. Y.C. Martin, "Quantitative Drug Design", Marcel Dekker, Inc., New York, 1978. V.E. Golender and A.B. Rozenblit, "Computer-Assisted Drug Design", Zinathe Press, Riga, U.S.S.R. 1978 (in Russian). A.J. Stuper, W.E. Brugger, and P.C. Jurs, "Computer Assisted Studies of Chemical Structure and Biological Function", Wiley-Interscience, New York, 1979. W.J. Dunn, in "Annual Reports in Medicinal Chemistry", Vol. 8, R.V. Heinzelman (Ed.), Academic Press, New York, 1973. R.D. Cramer, in "Annual Reports in Medicinal Chemistry", Vol. 11, F.H. Clarke (Ed.), Academic Press, New York, 1976. C. Hansch, in "Advances in Linear Free Energy Relationships", Vol. 2, N.R. Chapman and J. Shorter (Eds.), Plenum Press, New York, 1979. P.N. Craig, in "Biological Correlations -- The Hansch Approach", W. Van Valkenburg (Ed.), American Chemical Society, Washington, D.C. 1972. W.G. Richards and M.E. Black, in "Progress in Medicinal Chemistry", Vol. 11, G.P. Ellis and G.B. West (Eds.), American Elsevier, New York, 1975. R.E. Christoffersen, in "Quantum Mechanics of Molecular Conformations", B. Pullman (Ed.), Wiley, New York, 1976. G.L. Kirschner and B.R. Kowalski, in "Drug Design", Vol. VIII, E.J. Ariens (Ed.), Academic Press, New York, 1978. N.J. Nilsson, "Learning Machines", McGraw-Hill, New York, 1965. E.A. Patrick, "Fundamentals of Pattern Recognition", Prentice-Hall, Englewood Cliffs, N.J., 1972. H.C. Andrews, "Introduction to Mathematical Techniques in Pattern Recognition", Wiley-Interscience, New York, 1972. J.T. Tou and R.C. Gonzalez, "Pattern Recognition Principles", Addison-Wesley, Reading, Mass., 1974. V.L. Tal'roze, V.V. Rasnikov, and G.D. Tantsyrev, Doklady Akademii Nauk SSSR , 159(1), 182 (1964). P.C. Jurs, B.R. Kowalski, and T.L. Isenhour, Anal.Chem., 41, 21 (1969).

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22. 23. 24. 25. 26. 27.

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28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. 47.

COMPUTER-ASSISTED DRUG

DESIGN

P.C. Jurs and T.L. Isenhour, "Chemical Application of Pattern Recognition", Wiley-Interscience, New York, 1975. B.R. Kowalski, Anal. Chem., 47, 1152A (1975). M.L. McConnell, G. Rhodes, U. Watson, and M. Novotny, Jour. Chrom. , in press. J.S. Wishok and M.C. Archer, Brit. Jour. Cancer , 33, 307 (1976). G.M. Singer, H.W. Taylor, W. Lijinky, Chem.-Biol. Interactions , 19, 133 (1977). I.A. Smith, G.D. Berger, P.G. Seybold, and M.P. Serve, Cancer Res. , 38, 2968 (1978). J.S. Wishnok, M.C. Archer, A.S. Edelman, and W.M. Rand, Chem.-Biol. Interactions , 20, 43 (1978). L.B. Kier, J.R. Simons, L.H. Hall, Jour. Pharm. Sci. , 67, 725 (1978). A.J. Hopfinger and G. Klopman, Chem.-Biol. Interactions , in press. W.J. Dunn III and S. Wold, Jour. Med. Chem. , 21, 1001 (1978). C. Hansch and T. Fujita, Jour. Amer. Chem. Soc. , 86, 1616 (1964). R. Franke, Mol. Pharmacol. , 5, 640 (1969). P.C. Jurs, J.T. Chou, and M. Yuan, Jour. Med. Chem. , in press. A.J. Stuper and P.C. Jurs, Jour. Chem. Infor. Comp. Sci. , 16, 99 (1976). A.J. Stuper, W.E. Brugger, and P.C. Jurs, in "Chemometrics: Theory and Practice", B.R. Kowalski (Ed.), American Chemical Society, Washington, D.C., 1977. L.B. Kier and L.H. Hall, "Molecular Connectivity in Chemistry and Drug Research", Academic Press, New York, 1976. W.J. Murray, Jour. Pharm. Sci. , 66, 1352 (1977). G.R. Parker, Jour. Pharm. Sci. , 67, 513 (1978). M. Randic, G.M. Brissey, R.B. Spencer, and C.L. Wilkins, "Computers in Chemistry", submitted. A.J. Hopfinger, "Conformational Properties of Macromolecules", Academic Press, New York, 1973. G. Del Re, Jour. Chem. Soc. , 4031 (1958). A. Leo, P.Y.C. Jow, C. Silipo, and C. Hansch, Jour. Med. Chem. , 18, 865 (1975). C. Hansch and A. Leo, in "Substituent Constants for Correlation Analysis in Chemistry and Biology", John Wiley and Sons, Inc., New York, in press. J.T. Chou and P.C. Jurs, Abstract, 176th American Chemical Society National Meeting, Miama, Fla., September 1978. J.T. Chou and P.C. Jurs, Jour. Chem. Infor. Comp. Sci. , submitted for publication. W.J. Dixon (Ed.), "Biomedical Computer Programs", University of California Press, Berkeley, California, 1973.

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4.

48. 49. 50. 51. 52. 53.

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54. 55. 56. 57. 58. 59. 60. 61. 62. 63.

JURS

ET

AL.

Pattern Recognition

129

S.L. Morgan and S.N. Deming, Anal. Chem. , 46, 1170 (1974). G.L. Ritter, S.R. Lowry, C.L. Wilkins, and T.L. Isenhour, Anal. Chem. , 47, 1951 (1975). G.S. Zander, A.J. Stuper, and P.C. Jurs, Anal. Chem. , 47, 1085 (1975). Mark Yuan and P.C. Jurs, in preparation. A. Dipple, in "Chemical Carcinogens", C. Searle (Ed.), American Chemical Society, Washington, D.C. 1976. J. McCann, E. Choi, E. Yamasaki, and B.N. Ames, Proc. Nat. Acad. Sci. USA , 72, 5135 (1975). J.C. Arcos and M.F. Argus, "Chemical Induction of Cancer", Vol. IIa, Academic Press, New York, 1974. J.C. Arcos and M. Arcos, Prog. Drug Res. , 4, 407 (1962). J.T. Chou and P.C. Jurs, Jour. Med. Chem. , submitted. P.N. Magee, R. Montesano, and R. Preussmann, in "Chemical Carcinogens", C.E. Searle (Ed.), American Chemical Society, Washington, D.C., 1976. K. Lee, B. Gold, and S.S. Mirvish, Mutation Res. , 48, 131 (1977). C. Nagata and A. Imamura, Gann , 61, 169 (1970). B. Testa, J.C. Bunzil, and W.P. Purcell, Jour. Theo. Biol. , 70, 339 (1978). B. Testa and D. Mihailova, Jour. Med. Chem. , 21, 683 (1978). S.S. Hecht, C.B. Chen, and D. Hoffman, Cancer Res. , 38, 215 (1978). A.M. Camus, M. Wiessler, C. Malaveille, H. Bartsch, Mutation Res. , 49, 187 (1978).

RECEIVED June 8, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

5 Chance Factors in QSAR Studies JOHN G. TOPLISS and ROBERT P. EDWARDS

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch005

Schering-Plough Research Division, Bloomfield, NJ 07003

­

During the past decade quantitative structure -activity relationships (QSAR) have emerged as an im­ portant tool in drug design ( 1 ) . The role of the computer has been essential in allowing practical use of s t a t i s t i c a l methods such as multiple regression analysis (2). However, there is a risk of arriving at fortuitous correlations when too many variables are screened relative to the number of available ob­ servations. In this regard a critical distinction must be made between the number of variables screened for possible correlation and the number which actu­ ally appear in the regression equation. By way of i l l u s t r a t i o n take a case where there are ten observations and corresponding activity values A to Α and eight variables V to V are con­ sidered. Multiple regression analysis yields equa­ tion (1) where r = 0.85, F = 19.8 (p < 0.005) and 1

10

1

8

2

2,7

A = aV1 + bV + c 2

(1)

V and V are each significant at the level p < 0.01. However, the s t a t i s t i c a l test for significance of the equation only relates to the variables included in the actual correlation equation and does not take account of the fact that eight variables were screened for possible correlation. It is clear that the greater the number of variables which are screened for possible inclusion the greater w i l l be the prob­ ability that a chance correlation w i l l occur. The p value of < 0.005 for the equation shown overstates to some extent the probability that the relationship given by the equation is real rather than occurring by chance. The question is how misleading is this p value? The studies to be described w i l l attempt to provide some answer to this question. 1

2

0-8412-0521-3/79/47-112-131$05.00/0 © 1979 American Chemical Society

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DESIGN

E a r l i e r work on t h i s problem was r e p o r t e d some y e a r s ago (^). However, t h e s e s t u d i e s were t o o l i m i t ­ ed i n scope t o p r o v i d e more t h a n a d e m o n s t r a t i o n t h a t i n d e e d t h e r e was a problem from chance c o r r e l a t i o n s under c e r t a i n c o n d i t i o n s and t o p r o v i d e v e r y g e n e r a l guidelines. A c c o r d i n g l y , i n view o f t h e i n t e r e s t i n t h i s problem f o l l o w i n g p u b l i c a t i o n o f t h e e a r l i e r study, p l a n s were made t o g e n e r a t e more e x t e n s i v e and d e t a i l e d data.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch005

Method The b a s i c approach was t o s e t up a l a r g e number and wide range o f s i m u l a t e d c o r r e l a t i o n s t u d i e s u s i n g random numbers f o r b o t h o b s e r v a t i o n s and s c r e e n e d v a r i a b l e s and a s s e s s t h e i n c i d e n c e and degree o f any resulting correlations. Computer System. The program used was d e v e l o p e d by m o d i f y i n g an e x i s t i n g FORTRAN M u l t i p l e R e g r e s s i o n A n a l y s i s Program (BMD 02R), t h e essence o f t h e modi­ f i c a t i o n s b e i n g t o g e n e r a t e t h e d a t a t o be a n a l y z e d u s i n g a pseudo-random number g e n e r a t o r and t o accumu­ l a t e s t a t i s t i c s from each o f t h e i n d i v i d u a l simula­ t i o n s and produce output r e p o r t s , f r e q u e n c y d i s t r i ­ b u t i o n s and summary t a b l e s . The program was r u n on an IBM 560/158 computer p e r f o r m i n g under 0S/VS2. Random Number G e n e r a t o r . The pseudo-random num­ b e r s were g e n e r a t e d u s i n g t h e IBM RANDU s u b r o u t i n e ( k ) which employs t h e M u l t i p l i c a t i v e C o n g r u e n t i a l Method and r e t u r n s a v e c t o r o f random numbers, each u n i f o r m l y d i s t r i b u t e d i n t h e range 0 t o 1. The random numbers were s c a l e d by a f a c t o r o f 1000. S t a r t i n g from a u s e r - d e f i n e d seed v a l u e , RANDU gen­ e r a t e s a stream o f pseudo-random numbers and w i l l produce 2 terms b e f o r e r e p e a t i n g . By comparison of t h e o b s e r v e d as a g a i n s t t h e e x p e c t e d f r e q u e n c y d i s t r i b u t i o n ( u n i f o r m ) o f numbers, RANDU i s an ade­ quate pseudo-random number g e n e r a t o r . To b e t t e r approximate pure randomness each computer r u n had a d i f f e r e n t e x t e r n a l l y imposed i n i t i a l seed v a l u e . I n a d d i t i o n o n l y e v e r y f o u r t h pseudo-random number was sampled from t h e stream. 1

2 9

Computer Program Methodology. The f i r s t s t e p i n each s i m u l a t i o n i s t o g e n e r a t e t h e d a t a m a t r i x w i t h r rows (one f o r each o b s e r v a t i o n ) and η + 1 columns (n independent v a r i a b l e s and one dependent). The v a l u e s o f r and η a r e s p e c i f i e d when t h e program i s

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch005

5.

TOPLiss A N D

EDWARDS

QSAR Studies

133

run. The d a t a are t h e n a n a l y z e d u s i n g a stepwise M u l t i p l e R e g r e s s i o n Technique ( 2 ) . At each stage o f t h i s p r o c e d u r e the independent v a r i a b l e most h i g h l y c o r r e l a t e d w i t h the dependent v a r i a b l e i s brought i n t o the model p r o v i d e d t h a t the p a r t i a l F - t e s t v a l u e f o r t h a t v a r i a b l e i s s i g n i f i c a n t at the 10$ l e v e l . Each independent v a r i a b l e i n the r e g r e s s i o n model i s t h e n re-examined t o see i f i t i s s t i l l making a s i g n i f i c a n t c o n t r i b u t i o n . Any v a r i a b l e whose p a r t i a l F - t e s t v a l u e i s not s i g n i f i c a n t at the 10$ l e v e l i s dropped from t h e model. T h i s p r o c e s s c o n t i n u e s u n t i l no more v a r i a b l e s e n t e r the model and none are r e j e c t ed. From each s i m u l a t i o n , the number o f v a r i a b l e s e n t e r i n g the r e g r e s s i o n (zero t o n) i s s t o r e d as w e l l as the r s t a t i s t i c i n the case o f at l e a s t one v a r i a b l e e n t e r i n g the r e g r e s s i o n a n a l y s i s . T h i s whole p r o c e s s i s r e p e a t e d f o r each s i m u l a t i o n , the number o f s i m u l a t i o n s t o be c a r r i e d out b e i n g s p e c i f i e d when the program i s run. The r e s u l t s o f a l l the simulat i o n s are t h e n c o n s o l i d a t e d t o g i v e the f o l l o w i n g statistics : (1) The number and r e l a t i v e f r e q u e n c y f o r 0, 1, 2, 3 e t c . v a r i a b l e s e n t e r i n g the r e g r e s s i o n a n a l y s i s . (2) The number and r e l a t i v e f r e q u e n c y f o r at l e a s t one v a r i a b l e e n t e r i n g the r e g r e s s i o n a n a l y s i s . (3) F o r each s i g n i f i c a n t c o r r e l a t i o n o b s e r v e d (a) mean r s t a t i s t i c (b) median r s t a t i s t i c ( c ) minimum r s t a t i s t i c (d) maximum r statistic. (4) The number and r e l a t i v e f r e q u e n c y o f obs e r v e d c o r r e l a t i o n s by r interval: 1.0-0.9;0.9-0.8; 0.8-0.7 etc. 2

2

2

2

2

2

Scope o f Study. The number o f v a r i a b l e s s c r e e n e d was 3-15> 20, 30, ho and the number o f obs e r v a t i o n s was 5-30, 50, 100, 200, kOO, 600. Altog e t h e r some 300 c o m b i n a t i o n s o f v a r i a b l e s and observ a t i o n s were examined. The number of runs f o r each c o m b i n a t i o n ranged from 120-2190. I t should be noted t h a t the study was o r i g i n a l l y d e s i g n e d f o r f a r fewer combinations of v a r i a b l e s and o b s e r v a t i o n s and runs per combination. However, due t o the unexpected a v a i l a b i l i t y , f o r a s h o r t p e r i o d , of a computer which was b e i n g phased out, the scope o f the study was g r e a t l y expanded. Results Due to space l i m i t a t i o n s i t i s not f e a s i b l e t o p r e s e n t i n t a b u l a r form a l l o f the d a t a o b t a i n e d i n

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

134

COMPUTER-ASSISTED

DRUG

t h e study. However, T a b l e I p r o v i d e s an i l l u s t r a t i v e sample. The columns i n t h e t a b l e g i v e t h e number o f independent v a r i a b l e s , t h e number o f o b s e r v a t i o n s , the number o f r u n s , t h e f r e q u e n c y o f a chance c o r r e l a t i o n , t h e average number o f v a r i a b l e s e n t e r e d ( f o r those runs f o r which a t l e a s t one v a r i a b l e i s ent e r e d ) , t h e maximum, minimum and mean r v a l u e s , and the f r e q u e n c y o f those runs where r ^ 0 . 5 and ^ 0 . 8 . F o r t h e s i t u a t i o n w i t h t e n independent v a r i a b l e s s c r e e n e d and t e n o b s e r v a t i o n s , some t w o - t h i r d s o f t h e runs gave a c o r r e l a t i o n and f o r these an average o f 2.20 v a r i a b l e s e n t e r e d . R ranged from 0 . 2 8 t o 1.00 w i t h a mean v a l u e o f 0 . 6 k . Almost h a l f o f t h e t o t a l runs made gave c o r r e l a t i o n s w i t h r v a l u e s o f 0 . 5 o r h i g h e r w h i l e about one q u a r t e r o f t h e t o t a l runs made gave c o r r e l a t i o n s w i t h r ^ v a l u e s o f 0 . 8 o r h i g h e r . As t h e number o f o b s e r v a t i o n s i n c r e a s e d t h e r e was a downward t r e n d i n r v a l u e s so t h a t f o r 15 observat i o n s o n l y h^o o f t h e t o t a l runs gave c o r r e l a t i o n s w i t h r ^ . 0 . 8 and f o r 30 o b s e r v a t i o n s no c o r r e l a t i o n s w i t h r ^ 0 . 8 were found. F o r 20 v a r i a b l e s s c r e e n e d and o n l y 15 observat i o n s , p r a c t i c a l l y a l l o f t h e runs r e s u l t e d i n some l e v e l o f chance c o r r e l a t i o n w i t h about kklo o f t h e t o t a l runs r e s u l t i n g i n a c o r r e l a t i o n w i t h r ^ 0 . 8 . As t h e number o f o b s e r v a t i o n s i n c r e a s e d t o 30 the number o f runs y i e l d i n g c o r r e l a t i o n s w i t h r ^ 0 . 8 d e c l i n e d t o about 1#. P-values f o r t h e observed c o r r e l a t i o n s ranged from a minimum v a l u e o f 0.10 up t o 0 . 0 0 . A t t h i s p o i n t i t must be noted t h a t the degree o f chance c o r r e l a t i o n found i n t h i s study was subs t a n t i a l l y l e s s t h a n t h a t r e p o r t e d i n an e a r l i e r study (jj). Mean r v a l u e s averaged about o n e - h a l f those r e p o r t e d i n t h e e a r l i e r study, r a n g i n g from t h r e e - q u a r t e r s down t o o n e - q u a r t e r . The cause o f t h i s d i s c r e p a n c y c o u l d not be determined s i n c e t h e b a s i c r e c o r d s from t h e e a r l i e r study were not retained. However, i t must be c o n c l u d e d t h a t t h e e a r l i e r study was i n e r r o r . The p r e s e n t study was v e r y c a r e f u l l y checked and s e l e c t e d combinations setup and performed manually showed s i m i l a r r e s u l t s . From d a t a g e n e r a t e d i n t h e p r e s e n t study i t i s now p o s s i b l e t o answer t h e q u e s t i o n r a i s e d e a r l i e r c o n c e r n i n g the p - v a l u e o f e q u a t i o n 1. With t e n obs e r v a t i o n s and e i g h t s c r e e n e d v a r i a b l e s t h e expected f r e q u e n c y o f chance c o r r e l a t i o n s comes out t o be about 12#. Thus, t h e v a l i d i t y o f t h e c o r r e l a t i o n e q u a t i o n i s f a r l e s s c e r t a i n t h a n the r e p o r t e d p - v a l u e indicates. 2

2

2

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch005

DESIGN

2

2

2

2

2

2

2

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

ko

40

1.26 1.15

0.26 0.27 0.28

2190 2190 2190 120 398 2190 2190 120 398 398 2190 120 120 398 2190 2190 120 120 2190 1991 1991 1991 199 199

5 10 20 5 7 10 20 10 12 15 30 10 15 17 20 30 15 20 30 50 50 100 50 100

3 3 3 5 5 5 5 10 10 10 10 15 15 15 15 15 20 20 20 20 30 30 l . k l

o.ko

0.67 0.71 0.71 0.74 0.88 0.87 0.86 0.85 0.85 0.94 0.97 0.95 0.95 0.99 0.99 1. 00 1.00

O.kl

5.00 3.53 3.53 3.41 5.59 5.17 7. ik 7. ok

2.48

3.33 2.77 2.6l

k.k2

1.84

I.30 2.20 2.09 1.92

0.39

O.kk

1.87 1.5*

1.1k

AV. NO. VAR. ENTERED

FREQ. CHANCE CORR.

NO. RUNS

NO. OBS.

0.73 0.76 0.52 0.90 0. ^7

0.9k

1.00 1.00 0.98 0.97 0.86 1. 00 0.98

0.7k

1. 00 0.95 0.63 1. 00 1.00 0.99 0.79 1.00 1.00 0.98

R

2

02 0.03

0.0k

0.

0. Ok

0.65 0.30 0. Ik 0.6l 0.45 O.3O 0. Ik 0.28 0.23 0.18 0.08 0.26 0.19 0.l6 0.13 0. 08 0.17 0.13 0.08 0. Ok

MIN R

2

0.37 0.18 0.49 0.24

0.24

0.23 0.79 O.60 0.53 0.45 0.30 0.73 Ο.56 0.39

0.46

0.57

0.64

0.83 0.47 0.24 O.80 0.73 0. $k 0.28

MEAN R

u s i n g Random Numbers

MAX

Table 1 Correlations

). IND. VAR.

Data from S i m u l a t e d

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch005

2

0.34 0.11 0.76 0.58 0.29 0.03 0.19 0. 00 0.44 0.01

0.46

0.28 0.03 0.74 0.56

0.46 0.41

0.26 0.09 0.01 0.44 0.34 0.21 0.03

0.15 0. 01 0. 00 0.28 0.15 0. o4 0.00 0.23 0.14 0.04 0. 00 0. 54 0.28 0.14 0.06 0.00 0.44 0.17 0. 01 0.00 0. 00 0.00 0. 02 0. 00

2

FREQ. R > 0.8 0.5

136

COMPUTER-ASSISTED DRUG

The r e s u l t s a r e f u r t h e r i l l u s t r a t e d i n F i g u r e s 1-7· The r e l a t i o n s h i p between r and t h e number o f v a r i a b l e s s c r e e n e d f o r v a r y i n g numbers o f observa­ tions i s i l l u s t r a t e d i n Figure 1· I t can be seen t h a t f o r a c o n s t a n t number o f o b s e r v a t i o n s r i n ­ c r e a s e s as t h e number o f v a r i a b l e s s c r e e n e d i n c r e a s e s . A l s o , f o r a g i v e n number o f v a r i a b l e s screened, r i n c r e a s e s as t h e number o f o b s e r v a t i o n s d e c r e a s e s . In F i g u r e 2 t h e r e l a t i o n s h i p between the number o f o b s e r v a t i o n s and t h e p r o b a b i l i t y o f a chance c o r r e ­ l a t i o n w i t h t e n screened v a r i a b l e s f o r v a r i o u s r v a l u e s i s shown. From the graph c o r r e s p o n d i n g t o r ^ 0 , 8 i t may be seen t h a t the p r o b a b i l i t y o f en­ c o u n t e r i n g a chance c o r r e l a t i o n a t t h i s l e v e l i s about 22$ f o r t e n o b s e r v a t i o n s , r e a c h i n g zero f o r 23 observations. The graph shown i n F i g u r e 3 g i v e s t h e r e l a t i o n ­ s h i p between t h e number o f o b s e r v a t i o n s and t h e prob­ a b i l i t y o f a chance c o r r e l a t i o n w i t h r ^ 0 . 8 f o r f i v e , t e n and f i f t e e n v a r i a b l e s . Thus, f o r f i v e screened v a r i a b l e s t h e p r o b a b i l i t y o f e n c o u n t e r i n g a chance c o r r e l a t i o n i s about 22$ f o r s i x o b s e r v a t i o n s , 10$ f o r e i g h t o b s e r v a t i o n s , 3$ f o r t e n o b s e r v a t i o n s and 1$ f o r twelve o b s e r v a t i o n s , A g u i d e l i n e o f t e n s t a t e d i s t h a t a c e r t a i n num­ ber o f o b s e r v a t i o n s a r e r e q u i r e d i n o r d e r t o have much c o n f i d e n c e i n a g i v e n c o r r e l a t i o n e q u a t i o n . T h i s r u l e o f thumb i s d e f i c i e n t on two c o u n t s ; f i r s t , v a r i a b l e s screened r a t h e r than v a r i a b l e s i n c l u d e d i n the e q u a t i o n should be c o n s i d e r e d and second, t h e number o f o b s e r v a t i o n s p e r v a r i a b l e i s not a l i n e a r f u n c t i o n o f t h e number o f v a r i a b l e s as i t p e r t a i n s t o a s p e c i f i e d l e v e l o f chance c o r r e l a t i o n . In Figure h are p l o t t e d the number o f o b s e r v a t i o n s p e r v a r i a b l e a g a i n s t t h e number o f v a r i a b l e s f o r chance c o r r e l a ­ t i o n l e v e l s o f 1$ f o r r v a l u e s o f ] ^ 0 . 5 , 0 . 8 and 0 . 9 · C o n s i d e r i n g t h e r ^ 0 . 8 curve, t h e number o f obser­ v a t i o n s p e r v a r i a b l e i s 3 · 7 f o r t h r e e v a r i a b l e s drop­ p i n g t o 1.75 f o r t h i r t e e n v a r i a b l e s . F i g u r e 5 shows t h e r e l a t i o n s h i p between observa­ t i o n s and v a r i a b l e s f o r a chance c o r r e l a t i o n p r o b a b i l ­ i t y o f 1$ o r l e s s f o r v a r i o u s r l e v e l s . The l i n e a r r e l a t i o n s h i p s shown a r e each s t a t i s t i c a l l y s i g n i f i c a n t a t t h e ρ < 0.0001 l e v e l . T h i s graph p e r m i t s the de­ t e r m i n a t i o n o f t h e number o f o b s e r v a t i o n s r e q u i r e d t o s c r e e n , f o r example, t e n v a r i a b l e s w h i l e k e e p i n g t h e p r o b a b i l i t y o f e n c o u n t e r i n g a chance c o r r e l a t i o n w i t h r ^ 0 . 8 a t t h e 1$ l e v e l o r l e s s . From t h e graph i t can be e s t i m a t e d t h a t t h i s number o f o b s e r v a t i o n s i s about 20. F o r r ^ 0 . 9 , t h e number r e q u i r e d i s l e s s , 2

2

2

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2

2

2

2

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Figure 1. Rehtionship between mean r values and number of variables screened (number of observations: (V) 7; (O )10; (A) 15; (Π) 20; (0 ) 25; (Φ) 30; (M) 50; (V)100) 2

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Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch005

0.301-

N0. OBSERVATIONS

Figure 2. Rehtionship between number of observations and probability of a chance correlation (Pc) for 10 screened variables with r ^ 0.7 (O), 0.8 (A), and 0.9(H) 2

NO. OBSERVATIONS

Figure 3. Rehtionship between number of observations and probability of a chance correlation for 5 (O), 10 (A), and 15 (Q) screened variables with r ^ 0.8 2

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>4 Ο

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e

3h

10 15 NO. VARIABLES

20

Figure 4. Number of observations/number of variables as a function of number of variables for specified levels of chance correlation (Pc < 0.01: R > 0.5 (O); R > 0.8(A); R > 0.9(D)) 2

2

2

i at % 8

6

8

J

I

I L_

10 12 14 16 18 20 22 24 26 28 30 NO. OBSERVATIONS

Figure 5. Rehtionship between number of observations and number of variables for chance correlation level Pc ^ 0.01 with r ^ 0.7 (O), 0.8 (A), and 0.9 (\J) 2

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16· E x t r a p o l a t i o n o f t h e p r e v i o u s graph a l l o w s one ( F i g u r e 6 ) t o make s i m i l a r e s t i m a t i o n s f o r l a r g e r numbers o f screened v a r i a b l e s . Thus, some 56 obser­ v a t i o n s would be r e q u i r e d t o s c r e e n ko v a r i a b l e s w h i l e k e e p i n g t h e p r o b a b i l i t y o f e n c o u n t e r i n g a chance c o r r e l a t i o n with r 0 . 8 a t t h e 1$ l e v e l o r l e s s . The p r e c e d i n g graphs make p o s s i b l e t h e e s t i m a t i o n o f t h e number o f o b s e r v a t i o n s needed t o s c r e e n a spec­ i f i e d number o f v a r i a b l e s w h i l e m a i n t a i n i n g t h e prob­ a b i l i t y o f e n c o u n t e r i n g a chance c o r r e l a t i o n o f de­ f i n e d r l e v e l a t 1$ o r l e s s . I n F i g u r e 7 t h e graph shows t h e e f f e c t on t h e number o f r e q u i r e d observa­ t i o n s as t h e t o l e r a t e d chance c o r r e l a t i o n p r o b a b i l i t y i n c r e a s e s t o 5 o r 10$. A g a i n t h e d e p i c t e d l i n e a r r e l a t i o n s h i p s a r e each s t a t i s t i c a l l y s i g n i f i c a n t a t the ρ < 0.0001 l e v e l . Thus, f o r 10 v a r i a b l e s , 20 o b s e r v a t i o n s a r e needed a t a chance c o r r e l a t i o n l e v e l o f 1$ which reduces t o 15 a t t h e 5$ l e v e l and 13-14 at the 10$ l e v e l . Some l i m i t a t i o n s must be p o i n t e d out t o t h e approach d e s c r i b e d i n t h i s study f o r e s t i m a t i n g prob­ a b l e chance c o r r e l a t i o n l e v e l s . In actual p r a c t i c e s c r e e n e d v a r i a b l e s have v a r y i n g degrees o f c o l l i n e a r i t y and not i n f r e q u e n t l y some v a r i a b l e s a r e h i g h l y collinear. G e n e r a l l y , c o l l i n e a r i t y w i l l be more i n e v i d e n c e i n a c t u a l p r a c t i c e among a group o f s c r e e n e d v a r i a b l e s t h e n among random number s i m u l a t e d s c r e e n e d variables. To t h e e x t e n t t h a t t h i s o c c u r s i t has t h e e f f e c t o f r e d u c i n g t h e number o f independent v a r i a b l e s a c t u a l l y o p e r a t i v e as such. To r e f e r e n c e a group o f s c r e e n e d v a r i a b l e s used i n an a c t u a l problem w i t h t h e random number d a t a i t i s t h e r e f o r e suggested t h a t when the c o r r e l a t i o n c o e f f i c i e n t between two s c r e e n e d v a r i ­ a b l e s i s 0 . 8 o r h i g h e r , t h e n o n l y one o f t h e s e v a r i ­ a b l e s i s counted i n a r r i v i n g a t t h e e f f e c t i v e number o f independent v a r i a b l e s s c r e e n e d . T h i s approximate c o r r e c t i o n device should avoid s e r i o u s o v e r e s t i m a t i o n o f chance c o r r e l a t i o n e f f e c t s . A second l i m i t a t i o n has t o do w i t h use o f t h e s t e p w i s e m u l t i p l e r e g r e s s i o n method. T h i s method p r o b a b l y misses some c o r r e l a t i o n s and as such l e a d s t o some u n d e r e s t i m a t i o n o f t h e i n c i d e n c e o f chance correlations. O v e r a l l , the r e s i d u a l b i a s a f t e r c o r r e c t i o n f o r t h e c o l l i n e a r i t y e f f e c t tends t o c o u n t e r b a l a n c e t h e b i a s from use o f t h e s t e p w i s e r e g r e s s i o n method so t h e net e s t i m a t i o n e r r o r may not be t h a t l a r g e . about

2

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In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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Να OBSERVATIONS

Figure 6. Rehtionship between number of observations and number of variables for chance correlation level Pc $ζ 0.01 with r ^ 0.7 (O), 0.8 (A), and 0.9 (Q) (extrapolated) 2

J

I

I

I

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6

8

10

I

I

I

I

1—ι—ι—ι—ι

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12 14 16 18 20 NO. OBSERVATIONS

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30

Figure 7. Relationship between number of observations and number of variables with r ^ 0.80 at specified probability levels: Pc < 0.01 (O); Pc < 0.05 (A); Pc < 0.10 (Π) 2

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A p p l i c a t i o n s to Reported C o r r e l a t i o n Studies

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch005

I n the l i g h t o f t h e chance c o r r e l a t i o n phenomenon d e s c r i b e d , some comments w i l l be made on a number o f c o r r e l a t i o n s t u d i e s r e p o r t e d i n the l i t e r a t u r e which i n v o l v e d l a r g e numbers o f screened v a r i a b l e s . The f i r s t o f t h e s e r e p o r t e d by P e r a d e j o r d i _et a l . (6) concerned a quantum c h e m i c a l approach t o s t r u c ­ t u r e - a c t i v i t y r e l a t i o n s h i p s of t e t r a c y c l i n e a n t i b i o t ­ ics. The c o r r e l a t i o n e q u a t i o n (2) c o n t a i n e d seven i n ­ dependent v a r i a b l e s each s i g n i f i c a n t at the 1$ l e v e l log

κ]

=

18.3975+56.1733Qoio - 1.1063E

0 l l

+71.3254Q

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*

9 1 5 5 E

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+l8.3655E

+ l f 8 # 7 9 5 6 Q

0 i g

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C

(2) w i t h the o v e r a l l e q u a t i o n s i g n i f i c a n t at the 0.1$ level. The r v a l u e g i v e n was Ο.986 so t h a t the equa­ t i o n accounts f o r almost a l l o f the v a r i a n c e i n the data. There were 20 o b s e r v a t i o n s and some l 8 p o s s i b l e independent v a r i a b l e s were s c r e e n e d . The random num­ b e r s i m u l a t e d c o r r e l a t i o n d a t a g e n e r a t e d i n the cur­ r e n t study d i d not i n c l u d e the c o m b i n a t i o n o f 20 ob­ s e r v a t i o n s and 18 v a r i a b l e s . The c l o s e s t r e f e r e n c e p o i n t s were 20 o b s e r v a t i o n s and 20 v a r i a b l e s f o r which the i n c i d e n c e o f chance c o r r e l a t i o n s w i t h r ^ 0 . 9 was about 8$, and 17 o b s e r v a t i o n s and 15 v a r i a b l e s w i t h a 5$ chance c o r r e l a t i o n i n c i d e n c e . The approximate r i s k of a chance c o r r e l a t i o n i s t h e r e f o r e 5-8$. The r e p o r t e d c o r r e l a t i o n e q u a t i o n , a l t h o u g h i t s t i l l may be v a l i d , thus appears f a r l e s s secure t h a n the r e p o r t e d p - v a l u e o f < 0.001 would i n d i c a t e . It s h o u l d be noted t h a t we are not s a y i n g t h a t t h e r e i s a 5-8$ p r o b a b i l i t y t h a t the r e p o r t e d e q u a t i o n c o u l d a r i s e by chance. We are s a y i n g t h a t from 20 observa­ t i o n s and 18 v a r i a b l e s t h e r e i s a 5-8$ p r o b a b i l i t y t h a t some c o r r e l a t i o n w i t h r ^ 0 . 9 c o u l d emerge from chance f a c t o r s a l o n e . Gibbons jet al.. ( j ) r e p o r t e d on Q u a n t i t a t i v e S t r u c t u r e - A c t i v i t y R e l a t i o n s h i p s among s e l e c t e d P y r i midinones and H i l l R e a c t i o n I n h i b i t i o n . The c o r r e l a ­ t i o n e q u a t i o n (3) a r r i v e d at was based on 17 observa2

2

2

Rplso = - 0 . 4 6 ( ± 0 . 1 ΐ ) τ τ r i n g + 8 . 9 2 ( ± 1 . 8 5 ) σ +0.0^5 (±0.008 )EMRtions,

contained

0.15

(3)

t h r e e independent v a r i a b l e s , had

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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r = 0,83 and a p - v a l u e o f < 0 . 0 1 . Some 20 v a r i a b l e s were s c r e e n e d f o r p o s s i b l e i n c l u s i o n which may be e q u i v a l e n t to about 18 v a r i a b l e s a l l o w i n g f o r c o l l i n earity factors. T h i s g i v e s the c o m b i n a t i o n 17 obser­ v a t i o n s and 18 v a r i a b l e s . The n e a r e s t reference p o i n t s a v a i l a b l e f o r chance c o r r e l a t i o n s are the com­ b i n a t i o n s 20 o b s e r v a t i o n s and 20 v a r i a b l e s and 15 ob­ s e r v a t i o n s and 15 v a r i a b l e s f o r which the c o r r e l a t i o n frequencies for r ^ , 0 . 8 are 17^ and 28^ r e s p e c t i v e l y . I t must, t h e r e f o r e , be c o n c l u d e d t h a t t h e r e i s a sub­ s t a n t i a l r i s k t h a t the r e p o r t e d e q u a t i o n i s s p u r i o u s i n sharp c o n t r a s t w i t h the r e p o r t e d p - v a l u e o f < 0 . 0 1 . A study by Timmermans and van Zwieten (J3) on QSAR i n C e n t r a l l y A c t i n g I m i d a z o l i n e s S t r u c t u r a l l y R e l a t e d t o C l o n i d i n e l e d to the development o f equa­ tion ( k ) . There were 27 o b s e r v a t i o n s and e f f e c t i v e l y 2

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch005

2

log

I/ED30 = -0.00032(±0.0008)(£Par) +0.105(±0.03)EPar 2

- 0.695(±0.17)ApKa°+5.333(±1.89)H0M0(P) (h)

+6.752(±2.25)EE(P)+2.1*94 η = 27,

r

2

= 0.91,

Ρ
10). They a l s o searched f o r c o r r e ­ l a t i o n s where a l l X v a l u e s were r e p l a c e d by random numbers and r e a l Y v a l u e s were r e t a i n e d . S i n c e t h i s does not p r e s e r v e t h e p a t t e r n o f c o l l i n e a r i t y p r e s e n t i n t h e r e a l X v a r i a b l e s e t t h i s l a t t e r p r o c e d u r e may not p r o v i d e as good an e s t i m a t e o f chance e f f e c t s . It i s also possible to replace selected X variables o n l y , w i t h random numbers. T h i s would be u s e f u l i n s i t u a t i o n s where i t i s s u s p e c t e d t h a t i n a c o r r e l a ­ t i o n e q u a t i o n c e r t a i n terms, e g . it, it were r e a l c o r r e l a t i o n s w h i l e o t h e r s were s p u r i o u s . " I n t h i s case, r e a l it and i t numbers would be r e t a i n e d and t h e o t h e r X v a r i a b l e s r e p l a c e d by random numbers. In e v a l u a t i n g c o r r e l a t i o n s f o r chance e f f e c t s a t t e n t i o n s h o u l d a l s o be p a i d t o whether some obser­ v a t i o n s have been dropped from t h e s e t i n o r d e r t o obtain a b e t t e r data f i t . T h i s i s a f a i r l y common o c c u r r e n c e and u s u a l l y g i v e s much h i g h e r r v a l u e s . However, sometimes t h e j u s t i f i c a t i o n g i v e n f o r drop­ ping the poorly f i t observations are questionable. The c o r r e l a t i o n e q u a t i o n o b t a i n e d from u t i l i z i n g a l l o f t h e o b s e r v a t i o n s ( i e . a f t e r adding back i n t h e dropped o b s e r v a t i o n s ) s h o u l d t h e r e f o r e be checked f o r p o s s i b l e chance c o r r e l a t i o n s t o g i v e a b e t t e r o v e r a l l evaluation o f the r e l i a b i l i t y o f the r e s u l t . 2

2

Summary The r e s u l t s o f t h e s t u d i e s d e s c r i b e d show t h a t chance c o r r e l a t i o n s a r e a r e a l phenomenon o c c u r r i n g when t h e number o f v a r i a b l e s s c r e e n e d f o r p o s s i b l e c o r r e l a t i o n i s l a r g e compared t o t h e number o f obser­ vations. F o r t h i s r e a s o n some c o r r e l a t i o n s a r e l e s s s i g n i f i c a n t t h a n t h e i r s t a n d a r d p- v a l u e s i n d i c a t e as has been demonstrated by r e f e r e n c e t o some r e p o r t e d correlations. The p r e s e n t study p r o v i d e s g u i d e l i n e s f o r t h e approximate i n c i d e n c e o f chance c o r r e l a t i o n s a t s p e c i f i e d r v a l u e s f o r v a r i o u s combinations o f obser­ v a t i o n s and s c r e e n e d v a r i a b l e s . Specific correlations o b t a i n e d under c o n d i t i o n s where t h e g u i d e l i n e s i n d i ­ c a t e an a p p r e c i a b l e r i s k o f chance c o r r e l a t i o n s s h o u l d be i n d i v i d u a l l y checked as d e s c r i b e d . 2

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F i n a l l y , i t s h o u l d "be p o i n t e d out t h a t t h e r e i s no i n t e n t i o n o f a d v o c a t i n g c o r r e l a t i o n s t u d i e s o n l y under c o n d i t i o n s where t h e r e i s a m i n i s c u l e r i s k o f chance c o r r e l a t i o n s . However, t h e importance o f having a true idea o f the r e l i a b i l i t y of a c o r r e l a ­ t i o n equation i s obvious. I t i s one t h i n g t o d e v e l o p and use a c o r r e l a t i o n e q u a t i o n which i s known t o be somewhat tenuous b u t q u i t e another t o b e l i e v e t h a t i t has a s o l i d f o u n d a t i o n when i n f a c t i t has n o t .

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch005

Acknowledgement s The a u t h o r s a r e i n d e b t e d t o L. Weber f o r a s s i s ­ tance i n d a t a t a b u l a t i o n and t o M. M i l l e r and A. Saltzman f o r h e l p f u l d i s c u s s i o n s .

Literature Cited 1. 2. 3. 4.

Martin, Y. C . , "Quantitative Drug Design", Marcel Dekker, Inc., New York, 1978. Draper, N. R., and Smith, H . , "Applied Regression Analysis", Wiley, New York, 1966. Topliss, J . G . , and Costello, R. J., J . Med. Chem. ( 1 9 7 2 ) , 15, 1066. International Business Machines Corporation, "System/360 Scientific Subroutine Package, Version III, Programmer's Manual, Program Number 360A-CM-03X" Manual GH20-0205-4 (Fifth Edition), IBM Corporation, White Plains, New York, August 1970.

5.

6. 7. 8. 9.

International Business Machines Corporation, "Random Number Generation and Testing,, Manual G20-8011, IBM Corporation, White Plains, New York. Peradejordi, F . , Martin, A. N., and Cammarata, Α., J . Pharm. Sci. ( L 9 7 L ) , 60, 576. Gibbons, L. K., Koldenhoven, E. F., Nethery, R. E . , Montgomery, R. E., and Purcell, W. P., J . Agric. Food Chem. (1976), 24, 203. Timmermans, B. M. W. M., and van Zwieten, P. Α . , J. Med. Chem. ( 1 9 7 7 ) , 20, 1636. Kier, L. B., and Hall, L. H . , J. Med. Chem. (1977),

10.

20,

1631.

Kier, L. B., and Hall, L. H . , J. Pharm. Sci. (1978),

RECEIVED

67,

1409.

June 8, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

6 The Design of Transition State Analogs P. R. ANDREWS

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch006

Department of Physical Biochemistry, The John Curtin School of Medical Research, Australian National University, Canberra, A.C.T. 2600, Australia

The transition state of an enzymically catalyzed reaction is bound to the enzyme much more tightly than its substrate(s), and may therefore be used as a template for the design of potent and specific enzyme inhibitors (1,2,3,4). Such inhibitors are known as transition state analogues, and have considerable potential as highly selective drugs. They may, for example, be specifically designed to inhibit enzymes which are vital to abnormal or invading cells, but of no importance to the host. Alternatively they may take advantage of quantitative biochemical differences between normal and abnormal tissue. Two major phases may be distinguished in the design of transition state analogues. They are (i) determination of the transition state structure, and (ii) specification of stable molecules which mimic the geometric and electronic properties of the transition state. Determination of Transition State Structure Unlike the substrate(s) and product(s) of a reaction, transition state structures cannot be studied directly, and the structures employed in analogue studies are commonly derived from intuitive interpolations between reactant(s) and product(s) on the basis of an assumed reaction mechanism. The intermediates obtained in this way may differ radically from the actual transition states. Efforts to deduce transition state structures theoretically have until recently been retarded by the failure of even the more sophisticated molecular orbital treatments to predict accurate activation energies, and the need to avoid geometric and mechanistic assumptions has made the calculation of reaction pathways prohibitively expensive. The introduction of efficient gradient methods for minimizing energy with respect to all geometric parameters, coupled with the advent of faster computers, has now virtually overcome the latter problem, and careful parameterization of semiempirical molecular orbital methods has led to more 0-8412-0521-3/79/47-112-149$05.00/0 © 1979 American Chemical Society In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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accurate calculated energies. The use of computers to determine the structures of transition states for enzyme catalyzed reactions has thus become a r e a l i s t i c p o s s i b i l i t y . The Reaction Coordinate. To calculate the reaction pathway, an internal coordinate which varies monotonically from reactant(s) to product(s) i s chosen as the reaction coordinate,e.g. the length of a making or breaking bond may be used. The energies at various points along the reaction pathway are then obtained by constraining the reaction coordinate to appropriate fixed values while minimizing the energy with respect to a l l other geometric variables. The high point on the reaction pathway thus obtained provides an estimate of the location and structure of the transition state, which may then be precisely located and identified by minimizing the energy gradient with respect to a l l geometric variables, including the reaction coordinate (5). Because of the complexity of many reaction surfaces i t may sometimes be necessary to calculate reaction pathways for several starting geometries and reaction coordinates; a number of alternative transition state structures may thus be located. The lowest energy transition state obtained in this way i s appropriate to the gas phase reaction, and does not necessarily correspond to the transient species for the reaction i n solution. Similarly, there i s no v a l i d j u s t i f i c a t i o n for assuming that the pathway catalyzed by the enzyme i s the calculated minimum energy reaction pathway. There i s , however, good reason to suppose that one of the calculated low energy reaction pathways w i l l be that catalyzed by the enzyme. The calculations may thus provide two or more alternative reference reactions with their corresponding transition states, one of which w i l l be selectively stabilized at the active site of the enzyme. Calculation Methods. Of the alternative molecular orbital methods available, the MINDO/3 method (6) has proved especially successful for calculating reaction pathways (7). Dewar estimates that the relative energies of alternative transition states are predicted to within 5 kcal/mol, and that the structures of transition states are probably reproduced to a few hundredths of an Angstrom i n bond lengths, and a few degrees i n angles (7). Unresolved differences between the energies and geometries of the transition state structures obtained for bimolecular. reactions using ab initio, MINDO/3 and other techniques (8) suggest that any molecular orbital method must s t i l l be applied with caution, but provided that alternative reaction pathways within 5-10 kcal/mol of the minimum energy pathway are considered, i t seems l i k e l y that an accurate representation of the transition state structure for an enzyme catalyzed reaction w i l l be obtained using MINDO/3. Versions of MINDO/3 suitable for various computers are available from the Quantum Chemistry Program Exchange (9,10,11).

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For reactions involving large molecules, the time required to compute a reaction pathway with MINDO/3 remains prohibitive. The development of reliable empirical methods for preliminary studies of reaction surfaces w i l l be necessary to alleviate this problem.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch006

Design of Stable Analogues The long p a r t i a l bonds and abnormal hybridization of transition state structures preclude precise correspondence between the functional groups of an analogue and those of the transition state, but a range of plausible analogues can usually be derived by inspection of the transition state structure; additional alternatives may be obtained from chemical or crystal structure f i l e s . Choice of the best analogues for synthesis i s then based on a comparison of their molecular structures with that of the transition state. For this purpose, computed transition state structures and other points on the reaction pathway may conveniently be stored in a molecule library f i l e , either as cartesian coordinates or as geometric variables; i t may also be convenient to store a connectivity matrix, since the presence of p a r t i a l bonds i n the transition state structure may not be s e l f evident from the interatomic distances. Molecular Manipulation and Superimposition* To f a c i l i t a t e molecular comparisons, a variety of computer graphic techniques are available for three-dimensional manipulation and display of the stored structures in the library f i l e (12,13). In our laboratory l a t e r a l stereo pair views of either single line or b a l l and stick models are displayed on a Tektronix 4014 graphics terminal linked to a Univac 1100/42 computer. The three-dimensional images of the analogues, derived using standard geometric parameters (14,15), are superimposed on that of the transition state structure using interactive graphics routines to manipulate either molecule. We automate this process by running a stepwise minimization of the extent of misfit between the two molecules. Various functions may be used for the minimization, which i s carried out with respect to the six degrees of intermolecular rotational and translational freedom as well as appropriate conformational variables i n the analogue molecule. The simplest function appears to be the sum of the squares of the distances between corresponding atoms i n the two molecules. In our hands this function has proved most useful when hydrogen atoms are excluded, isoelectric groups are equated, and atoms separated by more than a given distance (e.g. 1 A) are a r b i t r a r i l y assigned a separation of that distance. Analogues which optimally match the transition state structure are chosen for synthesis, which may i t s e l f be computer assisted (Wipke, this Symposium) . Inhibitory a c t i v i t i e s against the enzyme may then be measured in vitro and/or in vivo, and

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structure-activity relationships determined. Design of further analogues may then prove desirable on the basis of these data. Example : Inhibition of Chorismate Mutase

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch006

The Claisen rearrangement of chorismate to prephenate, catalyzed by chorismate mutase, i s illustrated below. It

is the f i r s t specific step i n the biosynthetic pathways leading to tyrosine and phenylalanine in bacteria and other organisms (16). The enzyme i s absent i n man and thus provides a potential target for bacteriostatic action, although this potential i s limited by the a b i l i t y of bacteria to scavenge aromatic amino acids i n the bloodstream. The enzyme provides a clear example of the design principles described above, i l l u s t r a t i n g both advantages and limitations of most of the techniques discussed. Transition State Calculation. MINDO/3 calculations have been used to describe the reaction surface for the isomerization of chorismate i n both the neutral and dianionic forms (17). Two alternative structures were obtained i n each case (Figure 1). One, which results from clockwise rotation of the sidechain around the breaking C-0 bond, adopts a chair-like configuration; the other results from anticlockwise rotation, which leads to a boat-like structure. Both are asymmetric structures in which the breaking C-0 bond (ca. 1.45 A) i s significantly shorter than the making C-C bond (ca. 1.95 A). The enthalpy difference between these alternative reaction pathways (

d

> d

Figure 3. PCILO (Row 1) and empirical (Row 2) optimized geometries of complexes of AMS with (a) methylcyclopropane; (b) benzene; (c) propene; (d) 2,3-dimethyfuran; and (e) 2-methylthiofuran

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between the two methods. T h i s geometry d i f f e r e n c e i s r e f l e c t e d i n the d i s p a r i t y i n the energy of t h i s complex obtained by the two methods. Relevance to Opiate A c t i v i t y and Antagonism Antagonist potencies measured i n v i t r o i n the guinea p i g ileum system or i n v i v o by extent of withdrawal i n addicted animals should c l o s e l y p a r a l l e l the a f f i n i t y of opiates f o r the receptor s i t e . Both antagonist potencies and s t e r o s p e c i f i c b i n d i n g constants have been measured f o r a number of N - s u b s t i t u t e d 5,9 dimethyl 2 hydroxy 6,7 benzomorphan analogues (14, 15, 32). Table I I I gives these values f o r the compounds s t u d i e d and shows the extent of c o r r e l a t i o n between the known a f f i n i t i e s and potencies f o r four analogues. Expanding t h i s l i s t to other N-substituents and other r i g i d opiate s e r i e s i n c r e a s e s the c o r r e l a t i o n , though a number of s i g n i f i c a n t d e v i a t i o n s occur (32). In the s e r i e s shown i n Table I I I only the N-substituent i s v a r y i n g . Thus the observed d i f f e r e n c e s i n b i n d i n g a f f i n i t i e s and antagonist potencies could be due d i r e c t l y to d i f f e r e n c e s i n the N-substituent i n t e r a c t i o n s with the receptor s i t e . The c a l c u l a t i o n s reported are an i n i t i a l attempt to determine the extent of i n t e r a c t i o n , i f any, of N-substituents with model a n i o n i c receptor s i t e s . Without the c o n s t r a i n t of a t t a c h i n g the s u b s t i t u e n t to the amine group of the o p i a t e , the e l e c t r o n i c f a c t o r s which c o n t r o l optimium i n t e r a c t i o n s could be more f u l l y explored. As already d i s c u s s e d , s t a b l e complexes were found f o r a l l the s u b s t i t u e n t s i n v e s t i g a t e d but with d i f f e r i n g s t a b i l i t i e s . Even though these compounds are unconstrained by the s t e r i c requirements imposed on them as N-substituents i n r i g i d o p i a t e s , i t i s nevertheless of some i n t e r e s t to compare the c a l c u l a t e d value of i n t e r a c t i o n energy of each compound with the measured a f f i n i t y and/or antagonist potency f o r the most c l o s e l y r e l a t e d benzomorphan analogue. In Table I I I , the compounds studied are l i s t e d i n order of the decreasing antagonist potency they confer as N-substituents of 5,9 dimethyl 2'hydroxy, 6,7 benzomorphans. C a l c u l a t e d s t a b i l i t i e s with both a n i o n i c s i t e s tend to f o l l o w the observed a f f i n i t i e s and p o t e n c i e s . The three most potent antagonists are c a l c u l a t e d to be the three most s t a b l e complexes with AMS and among the four most s t a b l e complexes with AMP. On the other hand, the twa n e a r l y pure agonist have the s m a l l e s t i n t e r a c t i o n energy. For the remaining compounds, the strong complex found f o r 2-methythiofuran does not c o r r e l a t e w e l l with i t s weak antagonism, although there i s no measured b i n d i n g constant f o r t h i s compound. The b i n d i n g constant of pentazocine i s l e s s than expected from the c a l c u l a t e d s t a b i l i t i e s of benzene i n t e r a c t i n g with an a n i o n i c receptor s i t e . In phenazocine, with a phenethyl r a t h e r than phenyl s u b s t i t u e n t , the benzene

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch011

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r i n g might be too f a r away from the a n i o n i c s i t e f o r optimimum interaction. S i m i l a r trends, but with some d i f f e r e n c e s are seen i n the s t a b i l i t i e s c a l c u l a t e d by the e m p i r i c a l method. With the exception of the cyclopropylmethane, the main discrepancy i s the r e l a t i v e l y l a r g e energy c a l c u l a t e d f o r the 2,3 - dimethylfuran. The s t a b i l i z a t i o n energies of the AMS complexes c a l c u l a t e d by the e m p i r i c a l method c o r r e l a t e more with the measured a f f i n i t i e s and antagonist potencies than those f o r the AMP complexes. A d d i t i o n a l l y , more s t a b l e complexes with AMS a r e found by the e m p i r i c a l method than by the PCILO method. Taken together, the r e s u l t s of both methods i n d i c a t e that e i t h e r the phosphate or s u l f a t e anion i s a reasonable model f o r the a n i o n i c o p i a t e receptor s i t e . The r e s u l t s obtained i n t h i s study, while not d e f i n i t i v e , have been encouraging enough to allow us to continue these s t u d i e s using the same methodology. The next step w i l l be to r e c a l c u l a t e the optimum energies and geometries of the methyl phosphate and s u l f a t e anions i n t e r a c t i n g with these compounds as N-substituents of the p i p e r d i n e r i n g of r i g i d o p i a t e s . I f the two conformer hypothesis of mixed a g o n i s t / antagonist behavior i s c o r r e c t then: a) N-substituent analogues with l i t t l e or no agonist potency should have one w e l l defined, r a t h e r s t a b l e complex b) N-substituent analogues which ftite n e a r l y pure a g o n i s t s should a l s o have one optimum complex, d i s t i n c t from that of a pure antagonist and c) N-substituent analogues with mixed a g o n i s t / a n t a g o n i s t behavior should have two d i s t i n c t s t a b l e r e c e p t o r complexes. The more d i f f e r e n t the s t a b i l i t y of each, the more d i s p a r a t e the a g o n i s t / a n t a g o n i s t potency r a t i o f o r a given o p i a t e should be. The g r e a t e r the s t a b i l i t y of the best complex, the l a r g e r the antagonist potency should be. Work i s now i n progress to t e s t t h i s hypothesis.

Acknowledgement The support of N a t i o n a l I n s t i t u t e of Drug Abuse Grant # DA 00770-03 and NASA Ames Interchange //NCA-OR 745-721 f o r t h i s work i s g r a t e f u l l y acknowledged. The authors a l s o wish t o acknowledge the use of the AIMS computer graphics system a t NASA AMES. Many thanks a l s o to Donald S. Berkowitz and W i l l i a m Maloney f o r help i n the i n i t i a l stages of t h i s study.

Abstract In this study both the PCILO and empirical energy methods were used to characterize intermolecular interactions of typical N-substituents of rigid opiates with model anionic receptor sites. Ammonium methylphosphate (AMP) and ammonium methylsulfate (AMS) were used as model anionic receptor sites. Interaction energies of eight compounds which, as N-substituents, modulate different antagonist/agonist potencies

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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in 5,9-dimethyl 2' hydroxy 6,7 benzomorphans were calculated. Stable Η-bonded and n-π complexes were obtained. These results suggest that such complexes could be involved in the mode of interaction of the rigid opiates at the receptor site and in their observed affinities and agonist/antagonist potency ratios.

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Literature Cited 1. Pert, C. B.; Snyder, S. H. Science, 1973, 179, 1011. 2. Simantov, R.; Snowman, A. M.; Snyder, S. H. Brain Res., 1976, 107, 650. 3. Simon, E. J.; Hiller, J. M.; Edelman, I. Proc. Nat. Acad. Sci. U. S. Α., 1973, 70, 1947. 4. Loewney, L. I.; Schilz, K.; Lowery, P. J.; Goldstein, A. Science, 1974, 183, 749. 5. Loh, H. H . ; Cho, T. M.; Wu, Y. C.; Way, E. L. Life Sci., 1974, 14, 2233. 6. Loew, G. H.; Jester, R. J . Med. Chem., 1975, 18, 105. 7. Loew, G. H.; Berkowitz, D. S.; Newth, R. C. J . Med. Chem. 1976, 19, 863. 8. Loew, G. H.; Burt, S. K. Proc. Nat. Acad. Sci. U. S. Α., 1978, 75, 10. 9. Jasinski, D. R.; Martin, W. R.; Hueldtke, R. Clin. Pharm. Ther., 1971, 12, 613. 10. Lewis, J . W.; Bentley, K. W.; Cowan, A. Annu. Rev. Pharm, 1971, 11, 241. 11. Kosterlitz, H. W.; Waterfield, A. A. Annu. Rev. Pharm., 1975, 15, 29. 12. Loew, G. H.; Berkowitz, D. S. J . Med. Chem., 1975, 18, 656. 13. DeGraw, J. J.; Lawson, J. Α.; Crase, J. L.; Johnson, H. L.; E l l i s , M.; Uyeno, E. T.; Loew, G. H.; Berkowitz, D. S. J . Med. Chem., 1978, 21, 415. 14. Merz, H.; Langbein, Α.; Stockhaus, K.; Walther, G.; Wick, H. in "Narcotic Antagonists", Vol. 8, M. C. Braude, L. S. Harris, E. L. May, J . P. Smith, J . E. Villarreal, Eds., Raven Press: New York, 1974; p.91 15. Kosterlitz, H. W.; Waterfield, Α. Α.; Berthoud, V. in "Narcotic Antagonists," Vol. 8, M. C. Braude; L. S. Harris, E. L. May, J . P. Smith, J . E. Villarreal, eds., Raven Press: New York, 1974, p.319. 16. Diner, S.; Malrieu, S. P.; Jordan, F . ; Gilliert, M. Theor. Chim Acta., 1969, 15, 100. 17. Lochman, R.; Weller, Th. Int. J . Quantum Chem., 1976, 10, 909. 18. Spurling, Τ. H.; Snook, I. K. Chem. Phys Letts., 1975, 32, 159. 19. Weller, Th. Int. J . Quantum Chem., 1977, 12, 805. 20. Lochman, R.; Hofman, H.J. Int. J . Quantum Chem., 1977, 11, 427.

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21. Burt, S.; Egan, J., McElroy, R. D. Compt. in Chem., 1979, submitted. 22. Momany, F. A.; Carruthers, L. M.; McGuire, R. F.; Scheraga, H. A. J . Phys. Chem., 1974, 78, 1595. 23. Millner, O. E.; Anderson, J. A. Biopolymers, 1975, 14 2159. 24. Jordan, F. A. J . Theo. Biol., 1973, 41, 375. 25. Coeckelenberg, Y . ; Hart. J.; McElroy, R. D.; Rein, R. Computers and Graphics, 1978, 3,9. 26. G i l l , P. E., Murray, W.; Pitfield, R. A. National Physics Laboratory Division and Numerical Analysis and Computation Depart. No. 11, 1972. 27. Burt, S. K.; McElroy, R. D.; Egan, J . E. Unpublished results. 28. Sutton, L. E. "Tables of Interatomic Distances in Molecules and Ions," The Chemical Society: London, 1965, 11; 1958, 8. 29. Pople, J.; Beveridge, D. "Approximate Molecular Orbital Thery"; McGraw-Hill: New York, 1970; p 111. 30. Karle, I. L . ; Gilardi, R. D.; Fratini, Α. V.; Karle, J . Acta Cryst, 1969, 85, 469. 31. Zefirov, Y. V.; Zorkii, P. Μ. Ζ. H. Strukit, Khim., 1976, 17, 994. 32. Ionescu, I; Klee, W.; Katz, R. in "The Opiate Narcotics," A. Goldstein, Ed., Pergamon Press: New York, 1975, p. 41. Received June 8, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

12 Functional Receptor Mapping for Modified Cardenolides: Use of the PROPHET System DOUGLAS C. ROHRER—Medical Foundation of Buffalo, Inc., Buffalo, NY 14203 DWIGHT S. FULLERTON and KOUICHI YOSHIOKA—School of Pharmacy, Oregon State University, Corvallis, OR 97331

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch012

ARTHUR H. L. FROM—Cardiovascular Division, Department of Medicine, Veterans Administration Medical Center, Minneapolis, MN 55417, and University of Minnesota, Minneapolis, MN 55455 KHALIL AHMED—Toxicology Research Laboratory, Veterans Administration Medical Center, Minneapolis, MN 55417, and Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455

Digitalis preparations have been used therapeutically in the management of cardiovascular disease for almost 200 years (1). Their ability to increase the contractility of the heart muscle (the inotropic activity) combined with the slowing of the heart rate (the chronotropic activity) resulting in a generally improved heart efficiency keep these drugs among the top ten prescribed even today (2). Unfortunately, these drugs are also extremely toxic, with cardenolide toxicity accounting for up to half of drug induced in-hospital deaths (3). When the dose level required to attain the desired therapeutic response has been administered, 60% of the toxic dosage has also been given (4). Clearly, the demonstrated importance of these types of drugs combined with the need for improvement in the therapeutic-toxic ration provides a strong incentive for their study and for reaching a better understanding of their mode of action. The pharmacological effects of the digitalis glycosides, [such as digitoxin (Ia) or digoxin (IIa)] and their genins [Ib or IIb] appear to be the result of the inhibition of the membrane-bound Na ,K -ATPase (5,6,7). Thus it has been suggested that the Na ,K -ATPase enzyme is the digitalis receptor or certainly very closely related to i t (7). This enzyme system is found in the plasma membranes of nearly a l l mammalian cells and is involved in the active transport of Na and K+ across the cell membrane. This transport process is particularly important in cardiac muscle cells where the transport process must occur prior to each heart contraction. A number of often conflicting models (8,9) have been proposed to describe the chemical and structural characteristics of a genin which govern its ability to inhibit the Na ,K -ATPase. Our earlier studies (10-18) have shown that none of these models has been able to consistently explain the activities of a number of the modified genins. A multi-disciplinary approach, including X-ray crystallography, +

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conformational energy calculations, organic synthesis and Na^K"*"ATPase inhibition studies has been used to find the direct rela­ tionship between genin structure and activity reported here.

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I.

Cardenolide Structural Studies

The structural and electronic characteristics of a molecule determine i t s a b i l i t y to bind to and/or cause a physiological response with a given receptor. As described i n the previous section, the old models for cardiac glycoside action did not account for the a c t i v i t y of the modified genins. To delineate the true nature of the structure-activity relationship of cardenolide genins, a thorough study of cardenolide structure was begun using X-ray crystallography and the graphic analytical features of the NIH PROPHET computer system. Digitoxigenin, l b , i s generally considered to be the car­ denolide prototype. Its detailed structural features were there­ fore of particular interest. Figure 1 shows i t s crystallographi c a l l y determined structure (19). The curved shape of the ster­ oid backbone caused by ois fusions between the A and Β rings and the C and D rings and the axial methyl substituents are common features of most genins. Most synthetic modifications of d i g i ­ toxigenin involve the 173-substituent. This substituent has generally been recognized to be a major contributor to receptor binding of digitoxigenin analogues. A l l of the natural genins including digitoxigenin, lb, have a 173-lactone substituent (see Table I: T., i i , and VIII) . The 38- and 143-hydroxyl substitu­ ents are also common structural features. Until recently, the 146-hydroxyl substituent has been considered necessary for binding (13). The molecular structures of 11 other cardenolides were determined crystallographically [Table I: l i b (14), III (18), IVa (16), V (18), VI (18), VII (18), VIII (20), IX (17)> X (18), XI (18) and XII (21)] and compared with the structure of digitoxigenin, lb (19), on the NIH PROPHET computer system. A l l of the genins i n this study were synthesized i n our laboratories (10,11,12,16^) from digitoxin, l a , - except for XII, a g i f t from Dr. Mitsuru Yoshioka, Associate Director of Research, Shionogi Research Laboratories, Osaka, Japan; IVa, a g i f t from Dr. Romano Deghenghi,Director of Research, Ayerst Laboratories, Montreal, Canada; and VIII and l i b which were obtained commercially. The synthesis of the methyl ester, VI, and the n i t r i l e , VII, follow the procedures reported previously (8). These structures to­ gether with the Na ,K -ATPase inhibition data were used to for­ mulate the structural and activity correlations to be presented. +

+

Major Structural Classification Based on Ring D A l l genins examined i n this study can be divided into classes with; (1) a f u l l y saturated steroid backbone (I -> VIII), (2) a 14-ene-steroid backbone ( IX + XI) or (3) an 8(14)-enesteroid backbone (XII). Crystallographic analysis of these genins revealed that the A and Β rings and most of the C rings are nearly identical. It therefore seems reasonable to assume that this constant portion of the molecule must f i t into the

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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(a)

261

(b)

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Figure 1. PROPHET (a) top and (b) side views of the molecular structure of digitoxigenin lb from cristallographie coordinates

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

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same location at the receptor site. Any structural (as l i s t e d above) or conformational variation i n the D-ring portion w i l l have a marked effect on the position of the 178-side group r e l a ­ tive to the constant portion and also influence the Na ,K -ATPase inhibitory potency.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch012

+

Saturated D-Ring Structures. Normally, saturated cardeno­ lide backbones are thought to be r i g i d structures with very l i t t l e conformational v a r i a b i l i t y . Analysis of the 10 crystal structures representing 8 different molecules, however, indicates that there i s unexpected conformational freedom i n the D rings of these molecules. Furthermore, there are conformational trends which can be linked to the nature of the 178-side group. There are three types of 178-side groups represented; the normal lac­ tone ring (structures, I II, and VIII), and the modified lactone rings with a substituent on a carbon adjacent to the bond to the backbone (structures III and IV) and the acyclic side chains (structures, V, VI and VII). The major classes of D-ring conformations are a C148-envelope, Figure 2a, where C14 i s displaced i n the 8 direction from the remaining four coplanar atoms and a C148/C15a-half chair, Figure 2b, where C14 and C15 are displaced i n the 8 and α direc­ tions respectively from the three atom plane formed by C13, C16 and C17. Since the symmetry of these conformational forms (a mirror plane in the envelope and a two-fold rotation axis in the half chair) i s manifested i n the intra ring torsion angles, the torsion angles can be used to evaluate the deviation of a given conformer from the ideal form (22). A plot of the asymmetry parameters representing the deviation from ideal C148-envelope symmetry, AC (C14), versus the deviation from ideal C148/C15ahalf chair symmetry, AC2(C17), i s given i n Figure 3. The asymmetry parameter i s zero when the conformer has the ideal symmetric conformation. From this plot, i t i s apparent that the D-ring conformations of the normal lactone structures are clus­ tered i n the C148-envelope region, while the modified lactone structures have D-ring conformations i n the C148/C15a-half chair region. The acyclic structures show a large amount of D-ring conformational freedom which probably results from the decreased strain i n the 178-side group. The D-ring conformation of V i s a C13a-envelope, VI i s a distorted C148/C15a-half chair, and VII i s a C13a/C148-half chair. It appears from these results that the D-ring of the modified lactone group has a highly preferred conformation as a result of the location of the substituent on the lactone ring. The normal lactone places some limitations on the D-ring conformation, but not as great as the modified lac­ tones. Finally, the acyclic side groups place few restrictions on the D-ring conformations. The effect these D-ring conformational differences have on the orientation of the 178-side group relative to the constant portion of the molecular are shown i n Figure 4. It i s apparent 9

g

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Modified Cardenolides

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Ο

4

8

12 16 AC (C14)

20

24

S

Figure 3. Correlated variation in ring D principle asymmetry parameters. The two-fold rotational asymmetry parameter &C (C ) is plotted vs. the mirror plane asymmetry parameter ^Cs(C ). 2

17

1!t

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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Ο ET a

Figure 4. PROPHET/FITMOL overlay of the D-ring regions in structures lib, IVa, and V showing the shift in location of the Πβ-bond associated with different saturated ring D conformations

(a)

(b)

Figure 5. PROPHET/FITMOL overlays of (a) lb and IX and (b) lb and XI showing the shift in the location of the ΙΊβ-side group associated with the pres­ ence of a C -C double bond in the D ring n

(a)

î5

(b)

Figure 6. (a) Top and (b) side views of the PROPHET/FITMOL overlays of lb and XII clearly showing the change in the overall backbone structure in XII associated with the presence of a Cs-C^ double bond

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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that the exocyclic C178 bond orientation changes dramatically with change in conformation. This change w i l l be amplified at each successive location out on the chain causing a substantial change i n the relative location of the functional oxygen, independent of differences in the nature of the side group. 14-Ene D-Ring Structures. The C14-C15 double bond i n these molecules restricts the D-ring conformation to a C17a-envelope. This observation i s consistent with the structures of other noncardenolide steroid molecules with a C14-C15 double bond (23,24). There are 3 structures with this type of D ring (IX, X> and XI). Figure 5 shows the marked effect of this D-ring conformation on the orientation of the 178-side group relative to the constant portion. 8(14)-Ene D-Ring Structure. Here the double bond i s i n the C ring, but i t s effect extends into the D ring. There i s only one cardenolide structure of this type available for comparison XII. The D-ring conformation i s a C17a-envelope, but the C8-C14 double bond i n ring C also affects the directionality of the 178-side group relative to the constant portion of the molecule (Figure 6). 178-Side Group Orientation The 178-side group also has rotational freedom about the C17-C20 bond. In order to explore this conformational freedom, relative conformational energies were calculated using a version of the CAMSEQ (25) program which was specially modified to be used in conjunction with the NIH PROPHET computer system (26). Starting with the crystallographic coordinates, the energy was evaluted at 10° rotation steps of the 178-side group while minimizing the nonbonded interaction with the C13 angular methyl by also allowing i t to rotate. No differences were found i n the locations of minima or shape of the curve when solvent ( i . e . water) interactions were included i n these calculations. In every case, the crystallographically observed conformation was at a potential energy minimum. Saturated D-Ring Structures. These calculations agree with earlier reported observations (17,27) that there are two energy minimum conformations for the normal lactone side group related by a rotation of approximately 180°. Figure 7 shows the resulting energy curves shifted so that the lowest energy i s zero kcal/mole. Since the differences i n the three energy curves result from relatively small differences i n the overall structures of the molecules, a curve representing both structural and conformational f l e x i b i l i t y can be generated by using the minimum energy at each side group orientation, Figure 7d. The very large energy barrier at 180° results from the steric interactions be-

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG

DESIGN

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266

Figure 7. Potential energy diagrams for the rotations of the normal lactone 17 βside group of (a) lb, (b) lib, (c) VIII, and (d) a combined diagram using the minimum energy at each conformational point. The arrows indicate the confor­ mations of the crystal structure.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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267

tween the hydrogens on C18 and C21, w h i l e the lower b a r r i e r at 0° i n v o l v e s the hydrogens of C22 with those on C18. The energy diagrams, F i g u r e 8, f o r the modified lactone r i n g s t r u c t u r e s i n d i c a t e much l e s s r o t a t i o n a l freedom than the normal lactone s t r u c t u r e s . T h i s i s a r e s u l t of the e x o c y c l i c s u b s t i t u e n t adjacent to the r o t a t i n g bond i n t e r a c t i n g with the s t e r o i d backbone. The t i l t of the lactone r i n g r e l a t i v e to the C17-C20 bond i n I I I caused by C20 being a t e t r a h e d r a l sp atom r a t h e r than planar s p a l s o e f f e c t s i t s energy p l o t . In each case, the conformations i n the c r y s t a l s t r u c t u r e (two independent s t r u c t u r e s f o r I I I and one f o r IV) a r e l o c a t e d i n the lowest and widest energy minimum r e g i o n o f the p l o t which should represent the l a r g e s t conformational populations. The a c y c l i c s t r u c t u r e s represent a somewhat more d i f f i c u l t problem s i n c e there i s an added degree o f freedom a s s o c i a t e d with the C21-C22 bond. However i n each of these s t r u c t u r e s the s i d e group atoms are n e a r l y coplanar. T h i s means that only the e i s o i d and t r a n s o i d o r i e n t a t i o n s f o r the C21-C22 bond need to be considered. The r e s u l t i n g c a l c u l a t i o n s , however, show no e f f e c t on the r o t a t i o n energy of the C17-C20 bond a s s o c i a t e d with changes i n the s i d e group C21-C22 conformation. Figure 9 shows the r e s u l t i n g energy diagrams f o r V, VI and VII. While the r e s u l t i n g curves have a number of minima, i n each case the X-ray conformation represents the p r e f e r r e d o r i e n t a t i o n - i . e . , i n the deepest and broadest minimum. 3

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch012

2

14-Ene D-ring S t r u c t u r e s . The energy curves f o r IX and X are i n t e r e s t i n g f o r s e v e r a l reasons. F i r s t , C20 i s an s p carbon r a t h e r than the s p carbon of a normal l a c t o n e . This means that the lactone r i n g i s not coplanar with the C17-C20 bond. Second, these C20 epimeric molecules have remarkably d i f f e r e n t Na+,K -ATPase i n h i b i t i o n a c t i v i t i e s which w i l l be discussed l a t e r . Figure 10 shows the energy diagram. In these molecules there i s only one p r i n c i p a l energy minimum conformat i o n , with one or more a d d i t i o n a l very narrow minima. Again the c r y s t a l s t r u c t u r e o r i e n t a t i o n s are i n the p r i n c i p l e energy minima, one s t r u c t u r e of _IX and two independent s t r u c t u r e s f o r X. The energy p l o t f o r XI, F i g u r e 10c, i s very s i m i l a r to the p l o t s obtained f o r the normal lactone s t r u c t u r e s ( l b , l i b , and VIII) discussed above. The C14-C15 double bond i n the D r i n g e v i d e n t l y does not g r e a t l y change the r o t a t i o n o f the s i d e groups. T h i s s t r u c t u r e , l i k e s t r u c t u r e s l i b and V I I I , has a d i s o r d e r e d 17$-side group. The two s i d e group o r i e n t a t i o n s of the c r y s t a l s t r u c t u r e represent two separate minima rather than a s i n g l e wide minimum on the energy p l o t . 3

2

+

8(14)-Ene D-Ring S t r u c t u r e . The change i n the s t e r o i d backbone and a s s o c i a t e d D-ring conformation g r e a t l y reduces the s t e r i c i n t e r a c t i o n s between the l a c t o n e r i n g hydrogens and the

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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268

COMPUTER-ASSISTED DRUG DESIGN

Figure 8. Potential energy diagrams for the rotation of the modified lactone Πβ-side group of (a) III and (b) IVa. The arrows indicate the conformations of the crystal structures. Compound III has two independent structural observations.

Figure 9. Potential energy diagrams for the rotation of the acyclic Πβ-side groups of (a)V, (b) VI, and (c) VII. The arrows indicate the conformations ob­ served in the crystal structure.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Modified Cardenolides

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Figure 10. Potential energy diagrams for the rotation of the ΙΊβ-side group of the C -C double bond D-ring structures: (a) IX, (b) X, and (c) XI. The arrows indicate the locations of the crystal structure conformations. Compound X has two independent conformations and XI has two alternate orientations. lk

ls

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

270

angular methyl group, see Figure 11. This means that the lactone ring has much greater orientational freedom than any of the other molecules studied. II.

Na^K^-ATPase Inhibition Studies

The I (molar concentration for 50% inhibition) in vitro Na ,K -ATPase inhibitory a c t i v i t i e s of the genins were determined using rat brain Na ,K -ATPase (E.C. 3.6.1.3), the preparation and assay of which have been reported previously by our laboratories (28,29). Rat brain enzyme was used i n these studies for two reasons: (1) the ease of preparation of high activity enzyme; and (2) the comparable sensitivity of most heart and brain enzyme preparations (29). I50 ranges for the less water soluble genins X and XII were extrapolated from their doseresponse curves at concentrations where they were completely soluble. Each genin was preincubated with the enzyme ten minutes, i.e. mixing steroid, enzyme, and media lacking K before adding KC£ to maximize inhibitory effects. Each genin was also tested without preincubation, however, there was l i t t l e or no difference i n I50 with or without preincubation for any of the genins except digoxigenin (lib) and strophanthidin (VIII). The added hydroxyl group of these genins decreased l i p o p h i l i c i t y with the result that binding to the enzyme i s concomitantly slower. 5 0

+

+

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+

+

+

Structure/Activity Correlation The results of the potential energy calculations show clearly that i n every case the crystallographically observed orientation of the 178-side group i s i n the energetically preferred conformation or conformations represented by the widest and deepest energy minima when calculated both with and without including a contribution for solvent water. Therefore, the crystallographically determined structure i s a suitable model for use in the biological a c t i v i t y and structural comparisons to follow. The PROPHET procedure FITMOL (30) was used to analytically superimpose the constant portion of structures l i b through XII upon the corresponding portion of the most active genin i n the series digitoxigenin, l b , using a least squares method. This permits a quantitative measure of the effects the modification of the 178-side group structure and variation i n the D-ring conformation have upon the functional groups, i n particular the position of the carbonyl oxygen. Comparison of the relative carbonyl oxygen separations obtained from FITMOL with the Na ,K -ATPase inhibition a c t i v i ties given in Table II revealed a striking correspondence. A simple linear regressior model was used to test the relationship between oxygen separation and the I50 data for Na ,K -ATPase +

+

+

+

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch012

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ROHRER ET AL.

Modified Cardenolides

Ο

Figure 11.

60

120 180 -120 -60 TORSION ANGLE (dcg.) C13- C17-C20-C22

271

Ο

The potential energy diagram for compound XII. The arrow indi­ cates the x-ray crystal structure conformation.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

+

Q

VI

7.0 x 10"

IVb

2.2 χ 10

1.2 χ 10

1.0 x 10

IVa

-6

7.0 x 10

III

III

7,0 x 10"

lib

1

7.0 x 10

-8

1,30

1,43

(C13-C17-C20-C21) -107.6 (C13-C17-C20-C21) -129.0

5.22

4.90

175.9 (C13-C17-C22-C23) -106.9

5,06

0.42 (2,31)

0,00

Carbonyl Oxygen Separations (%) obtained from FITMOL.

180,0

70.4 (alternate: -99.6)

76.3

•8 4.0 χ 10 -7 3,5 x 10

Ha

lb

la

Compound

X-Ray Structure Side Group Torsion Angle (°) C13-C17-C20-C22.

150 00 with 10 min. Preincubation,

Table II. Na ,K -ATPase Inhibition Data (I- ,M) and Side Group Structural Data for Compounds I to XII.

+

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch012

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

XII

XI

5

J

(3*6) x 10~ [extrapolated from

1.6 x 10~

data]

100.3

-102.4 (alternate:

-76.9)

4.61

3.76 (5.51)

5.67

-178.8

[extrapolated from I^g data]

(1-K3) x 10"

X

X

5.75

173.5

4

2.0 x 10"

IX

f

4.08

-144.2

0.88 (2.60)

5

-111.0)

7

85,0 (alternate :

(C13-C17-C20-C21) -129,9

Carbonyl Oxygen Separations (X) obtained from FITMOL.

7.5 χ 10"

VII

X

ο

to

COMPUTER-ASSISTED DRUG DESIGN

274 with p r e i n c u b a t i o n . shown i n Figure 12:

Eleven p o i n t s were found to f i t the

log I

5

0

= 0.459 D -

6.471

where D i s the r e l a t i v e carbonyl separations i n X. The r e ­ s u l t i n g r i s 0.993 and f o r t e s t of the r e g r e s s i o n r e l a t i o n s h i p , ρ = 0.0001. T h i s i n d i c a t e d that f o r each 2.28 the oxygen was d i s p l a c e d from that of d i g i t o x i g e n i n , a c t i v i t y drops by one order of magnitude [An e a r l i e r r e p o r t (15) with nine analogues showed n e a r l y the same r e l a t i o n s h i p , r = 0.994.] In genins l i b , V I I I and _XI where two 178-side group o r i e n ­ t a t i o n s were observed i n the c r y s t a l s t r u c t u r e , i t i s c l e a r that (as one would p r e d i c t ) only one i s p r e f e r r e d by the receptor. As shown i n Figure 13, the a l t e r n a t e conformations of these genins are more a c t i v e than can be explained by t h e i r carbonyl oxygen s e p a r a t i o n s . However, a n e a r l y p e r f e c t c o r r e l a t i o n Figure 12, e x i s t s f o r t h e i r other 178-side group conformations. The carbonyl oxygen separations f o r both s t r u c t u r e s of I I I and X are n e a r l y equal, F i g u r e 12, so e i t h e r conformation would be expected to have equivalent a b i l i t y to i n h i b i t Na ,K -ATPase. One s t r u c t u r e , e s t e r VI, i s more a c t i v e than i t s carbonyl oxygen s e p a r a t i o n would suggest. However, even i f t h i s p o i n t i s included i n the l i n e a r r e g r e s s i o n model, the r value i s s t i l l e x c e l l e n t (0.946). S e v e r a l p o s s i b i l i t i e s may e x p l a i n t h i s apparent anomaly and f u r t h e r s t u d i e s on VI are i n progress. This simple l i n e a r r e l a t i o n s h i p provides a q u a n t i t a t i v e explanation f o r a number of genins where other models have failed. In p a r t i c u l a r : 2

2

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch012

line

+

+

2

(A) The p r e d i c t e d a c t i v i t y of aldehyde, V, was up to 123 times higher than d i g i t o x i g e n i n based on previous models, but i t was found to be s l i g h t l y l e s s a c t i v e (10). F i g u r e 12 c l e a r l y shows that V s a c t i v i t y i s a d i r e c t r e s u l t of i t s carbonyl oxygen p o s i t i o n . The r i n g D con­ f o r m a t i o n a l d i f f e r e n c e and the s t r u c t u r a l d i f ­ ferences of the a c y c l i c 178-side group r e s u l t i n t h i s displacement. T

(B) I t has been g e n e r a l l y b e l i e v e d that the C20-C22 double bond i n the l a c t o n e r i n g has an a c t i v e r o l e i n i n h i b i t i n g the Na+,K+-ATPase (31,32). A lactone r i n g with an e x o c y c l i c double bond would be p r e d i c t e d to be even more a c t i v e than one with an e n d o c y c l i c double bond (32) and c e r t a i n l y more a c t i v e than one w i t h no double bond. However, IX and X, which should there­ f o r e be more a c t i v e than d i g i t o x i g e n i n , are much l e s s a c t i v e (11). Furthermore, the 20,22-

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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Modified Cardenolides

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3:

REL.CARBONYL OXYGEN SEPARATIONS [A]

Figure 12. Correction between the carboni/l oxygen separations relative to digitoxigenin, lb, and the log of the Na\K*-ATPase inhibition activity: (χ) mea­ sured 1 data; (+) I so data extrapolated from lower concentrations in which the analog was completely soluble 50

-3. η

Ο.

1.

2.

3.

4.

5.

6.

REL.CARBONYL OXYGEN SEPARATIONS[Â]

Figure 13. Correlation between relative carbonyl oxygen separations and the log of I so showing the oxygen separations associated with the alternate Ιΐβ-lactone orientations (A); carbonyl separation for VI (O)

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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dihydro analogues with no double bond though 100 times less active than digitoxigenin are more active than _IX and X (13). These activ­ i t y differences are readily explained by the conformational and structural effects on the position of the carbonyl oxygen; that i s , the C20-C22 double bond i s primarily serving a passive role i n Na+jK^-ATPase inhibition keeping the carbonyl oxygen i n the "right" position for maximal inhibitory effect (see Figure 12). (C) It has also been generally believed that the 148-hydroxyl greatly enhances the inhibition of Na ,K -ATPase (_5,6,1,8,9,33) . However, IX without the 148-hydroxy i s more active than the corresponding 148-hydroxy analogues III and i t s 20R stereoisomer (11). Figure 12 suggests that changes i n carbonyl oxygen position may account for these differences in activity. +

+

(D) The activity of genin IVb i s remarkably low (70 times lower than i t s 8-D-glucose analogue (IVa)). The effect of the glucose on the a c t i v i t y was not predicted by a recently proposed binding model (34). The structural correlation shown i n Figure 12, however, accurately f i t s the activity of genin IVb based on i t s modified lactone structure. Conclusions The data presented here are consistent with the following structural correlations of d i g i t a l i s genin-Na ,K+-ATPase inhib­ ition: +

(A) Rings A and Β with a ois fusion, most of the C ring, plus the axial methyl group form a structurally r i g i d CONSTANT PORTION of the molecule. (B) The saturated D rings have a great deal of conformational f l e x i b i l i t y with preferences influenced by the nature of the 178-side group. (C) There are substantial barriers to rotation of the 178-side group which provide orientational preferences modeled by the crystal

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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structures. (D) The acyclic α,8-unsaturated 178-side groups form acoplanar unit and are not as flexible as may have been thought. +

+

The relationship of these structural features to Na ,K ATPase inhibition and receptor modeling are:

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch012

(A) The CONSTANT PORTION of the genin molecules must a l l f i t onto a specific position on the receptor surface. (B) The 148-hydroxyl and C20-C22 double bonds do not seem to play as direct a role i n the i n ­ hibition as was previously thought. (C) The minimum energy conformation of the mole­ cule i s preferred at the receptor s i t e . (D) There i s a single carbonyl oxygen position relative to the CONSTANT PORTION which d i ­ rectly controls the activity (a 2.28 shift decreases the activity ten fold). Acknowledgement The authors are grateful to Miss Melda Tugac, Miss Gloria Del Bel and Mrs. Q. E. Bright for preparation of i l l u s t r a t i o n s and to Miss Kathleen Castiglione, Mrs. Brenda Giacchi and Miss Deanna Hefner for manuscript preparation. This work was sup­ ported i n part by Grant Number HL-21457 from the National Heart, Lung and Blood Institute and LM-02353 from the National Library of Medicine, the Oregon and Minnesota Heart Associations, and the Veterans Administration Medical Research Fund. The organi­ zation and analysis of the data base associated with this i n ­ vestigation were carried out i n part using the PROPHET system, a unique national resource sponsored by the NIH. Information about PROPHET including how to apply for access can be obtained from the Director, Chemical/Biological Information-Handling Program, Division of Research Resources, NIH, Bethesda, Maryland 20205.

Literature Cited 1. 2.

Withering, W., "An Account for the Fox Glove and Its Medical Uses"; (1785), in "Readings in Pharmacology"; Shuster, L. Ed.; Little Brown: Boston, 1962; p. 109. Pharmacy Times, "1977: Top 200 Drugs", 1978, April, p. 41.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

278 3. 4. 5. 6. 7. 8.

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9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26.

COMPUTER-ASSISTED DRUG DESIGN

Oglivie, R. I.; Ready, J . Can Med. Assoc. J., 1967, 97, 1450. Dreyfus, L. S.; Watanabe, Y. Seminars in Drug Treatment, 1972, 2, 179. Schwartz, Α.: Lindenmayer, G. E . ; Allen, J . C. Pharmacol. Rev., 1975, 27, 3. Flasch, H.; Heinz, N. Naunyn-Schmiedeberg's Arch. Pharma­ col., 1978, 304, 37. Akera, T. Science, 1977, 198, 569. Thomas, R.; Boutagy, J.; Gelbart, J . J . Pharm. Sci., 1974, 63, 1649. Guntert, T. W.; Linde, H. H. Experimentia, 1977, 33, 697. Fullerton, D. S.; Pankaskie, M. C.; Ahmed, K.; From, A. H. L. J . Med. Chem., 1976, 19, 1330. Fullerton, D. S.; Gilman, D. M.; Pankaskie, M. C.; Ahmed, K.; From, A. H. L.; Duax, W. L.; Rohrer, D. C. J. Med. Chem., 1977, 20, 841. Yoshioka, K.; Fullerton, D. S.; Rohrer, D. C. Steroids, 1978, 32, 511. Fullerton, D. S.; Yoshioka, K.; Rohrer, D. C.; From, A. H. L . ; Ahmed, K. J . Med. Chem., 1979, 22, in press. Rohrer, D. C.; Fullerton, D. S. Acta Crystallogr., Sect. B, submitted. Fullerton, D. S.; Yoshioka, K.; Rohrer, D. C.; From, A. H. L . ; Ahmed, Κ., Science, submitted. Fullerton, D. S.; Yoshioka, K.; Rohrer, D. C.; From, A. H. L . ; Ahmed, K. Mol. Pharmacol., submitted. Rohrer, D. C.; Duax, W. L.; Fullerton, D. S. Acta Crystal­ logr., Sect. B, 1976, 32, 2893. Rohrer, D. C.; Fullerton, D. S. Unpublished results. Karle, I. L . ; Karle, J . Acta Crystallogr Sect. Β 1969, 25, 434. Gilardi, R. D.; Flippen, J . L. Acta Crystallogr., Sect. B, 1973, 29, 1842. Gilardi, R. D.; Karle, I. L. Acta Crystallogr., Sect. B, 1970, 26, 207. Duax, W. L.; Weeks, C. M.; Rohrer, D. C. "Topics in Stereo­ chemistry", Vol. 9, Allinger, N. L. and E l i e l , E. L., Eds., Interscience: New York, NY, 1976; p. 271. Rohrer, D. C.; Strong, P. D.; Duax, W. L.; Segaloff, A. Acta Crystallogr., Sect. B, 1978, 34, 2913. Rohrer, D. C.; Duax, W. L.; Segaloff, A. Acta Crystallogr., Sect. B, 1978, 34, 2915. Weintraub, H. J. R.; Hopfinger, A. J . Int. J . Quantum Chem., Quantum Biol. Symp., 1975, 2, 203. Rohrer, D. C.; Lavin, M. "EDITMODEL"; in "Public Proce­ dures: A Program Exchange for PROPHET Users"; Wood, J. J., Ed., Bolt, Beranek and Newman, Inc.: Cambridge, MA, 1978.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

12. 27. 28. 29. 30. 31.

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32. 33. 34.

ROHRER ET AL.

Modified Cardenolides

279

Rohrer, D. C.; Fullerton, D. S. American Crystallographic Association Meeting Abstracts, 1978, Norman, Oklahoma, Abstract: J1. Quarforth, G.; Ahmed, K.; Foster, D. Biochem. Biophys. Acta, 1978, 526, 580. Ahmed, K.; Thomas, B. S. J . Biol. Chem., 1971, 246, 103. Rohrer, D. C.; Perry, H. "FITMOL"; in "Public Procedures: A Program Exchange for PROPHET Users"; Wood, J. J., Ed.; Bolt, Beranek and Newman, Inc.: Cambridge, MA, 1978. Thomas, R.; Boutagy, J.; Gelbart, A. J . Pharmacol. Exptl. Ther., 1974, 191, 219. Kupchan, S. M.; Ognyanov, I.; Moniot, J . L. Bioorg. Chem., 1971, 1, 24. Witty, T. R.; Remers, W. Α.; Besch, J r . , H. R. J . Pharm. Sci., 1975, 64, 1248. Thomas, R.; Allen, J.; Pitts, B. J . R.; Schwartz, A. Eur. J . Pharm., 1979, 53, 227.

Received June 8, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

13 Thyroid Hormones-Receptor Interactions: Binding Models from Molecular Conformation and Binding Affinity Data VIVIAN CODY

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch013

Medical Foundation of Buffalo, Inc., Buffalo, NY 14203

Thyroid hormones (Figure 1) are iodinated amino acids which are synthesized in the thyroid gland and travel through the gen­ eral circulation bound to serum proteins. While they have been shown to elicit a multitude of biological responses, the specific nature of their actions still remains unclear. However, as early as 1959 Jorgensen and his co-workers (1) had proposed that spec­ i f i c structural and stereochemical features of the thyroid hor­ mones were responsible for their hormone action. Because the thyroid hormones are transported through the bloodstream bound to the serum proteins thyroxine-binding globulin (TBG), thyrox­ ine-binding prealbumin (TBPA) and serum albumin (SA), and are bound to nuclear proteins which proportedly initiate hormone action (2), the question of conformational preferences becomes increasingly important. These special stereochemical properties arise from the steric influence of the diortho iodines upon the diphenyl ether conformation. Minimal steric interaction between the 3,5-iodines and the 2',6'-hydrogens is maintained when one ring is coplanar with, and the other perpendicular to, the plane of the two C-O ether bonds. This gives rise to two skewed conformations (Figure 2) which can be described by the torsion angles Φ(C5-C4-041-C1') and Φ' (C4-041-C1'-C6') of 0°/90° and 90°/0° for Φ/Φ', respec­ tively. Only the skewed conformer Φ/Φ' = 90°/0° has been ob­ served structurally, although the other has been implicated as an active conformer (3). This skewed conformation also imparts further stereospecific characteristics to the hormone Τ which contains only a single outer ring iodine. Because of the restricted rotation about the two diphenyl ether bonds, the chemically equivalent 3' and 5'iodines are conformationally distinct, giving rise to a distal (away) or proximal (near) conformation (Figure 3). To verify the importance of this conformational feature, numerous structural analogues of triiodothyronine were synthesized (4) in an effort to determine the biologically active conformer of T . 3

3

0-8412-0521-3/79/47-112-281$05.00/0 © 1979 American Chemical Society

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

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282

3,5 3',5'-TETRAIODO-L-THYRONINE (T ) ;

4

Figure 1.

3,5, 3'-TRIIODO-L-THYRONINE (T ) 3

Principal thyroid hormones thyroxine (T ) and triiodothyronine showing their molecular conformation and numbering scheme

ΑΝΤΙ - SKEWED ( φ / φ ' = 0 ° / 9 0 ° )

h

(T ) s

SKEWED ( φ / φ ' = 90° | 0°)

Figure 2. Two examples of the skewed (φ/φ' = 90°/0°) (right) and antiskewed (φ/φ' = 0°/90°) (left) diphenyl ether conformation of thyroxine. In each case the molecule is viewed perpendicular and parallel to the inner ring plane.

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Distal/Proximal 3'-Substituents The conformational requirements for a c t i v i t y and protein binding were investigated with 2',3'-dimethyl-3,5-diiodοthyro­ nine as the model for a d i s t a l conformer of T3 and 2',5'd ime t hy 1-3,5-diio do thyronine as the proximal model ÇL,5,6) . These studies showed that the d i s t a l analogue i s hormonally active, having 50% as much goiter-suppressing a c t i v i t y as T4 and 13% as much calorigenic effect as Τ3 (_5) . The proximal analogue shows only 1-2% as much activity as the d i s t a l analogue i n these tests. Similar results were obtained i n experiments using pure TBG or whole serum (_7) , indicating that the requirements for serum protein binding are the same as that required for hormone activity. The f i r s t nuclear magnetic resonance (NMR) studies of Τ3 f a i l e d to isolate two distinct spectra for the d i s t a l and proxi­ mal conformers (jB) . In addition, molecular orbital (MO) calcu­ lations predicted a high barrier to internal rotation about the diphenyl ether bonds (9). These data suggested that there was only one conformer present i n solution, presumably d i s t a l , since this was shown to be the active form of the hormone. However, the f i r s t crystal structure of T3 showed the 3'-I conformation to be proximal (10), inconsistent with available binding and a c t i v i t y data. This apparent dilema was resolved when further crystallographic data on Τ3 compounds became available (11,12,13,14,15). (See reference 11 for a detailed l i s t of thyroactive crystal structure studies.) These determinations show the 3'-I i n the d i s t a l conformation and further showed that either the d i s t a l or proximal conformer could be isolated by changing the crys­ t a l l i z i n g media (13,14). These data prompted further NMR and MO studies which showed a nearly equal distal/proximal ratio in solution (16) and a much smaller barrier to internal rotation (17). Thus these data have shown that the d i s t a l and proximal conformers are readily accessible i n solution and that the energy barrier to free rotation i s small enough so that the stereospecific conformer required by a receptor i s easily accessible. Cisoid/Transoid Conformation In addition to the conformational asymmetry of the outer phenyl ring, the thyronine nucleus possesses other conformational f l e x i b i l i t y (Figure 4). The preferred relative orientation (18) of the inner phenyl ring with respect to the amino acid (χ #90°) is such that the alanine side chain and the outer phenyl ring l i e either on the same side of the inner phenyl ring plane (eisoid) or on opposite sides of the inner ring plane (transoid) as shown i n Figure 5. Although the biological relevance of these conformers i s not known, they are observed with equal frequency. 2

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

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284

Figure 4.

Thyroxine with amino acid conformational parameters defined

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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13.

Figure 5.

Thyroid hormones illustrating transoid and eisoid overall conformation

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

286 Diphenyl Ether Conformation

As mentioned, the torsion angles φ and φ' describe the relative orientations of the two phenyl rings with respect to the C-O-C ether plane. While the bulky 3,5-iodines maintain a perpendicular ring arrangement (6), (the ideal skewed conforma­ tion i s φ/φ' = 90°/0°) analysis of these data suggest further correlations i n the parameters which influence the diphenyl ether conformation. The plot of φ versus φ (Figure 6) shows two lines corresponding to the eisoid and transoid conformers. The graph also shows that the data are grouped into two clusters, one near the skewed conformer (φ/φ = 90°/0°) and another, twistskewed, near φ = 108°, φ' = -28° or φ = -108°, φ' = 2 8 ° . Further inspection of those structures involved shows that the deamino acids (thyroformic, acetic, propionic) tend to be skewed (19) whereas the iodοthyronines are twist-skewed. These observations suggest that the α-amino nitrogen i s responsible for the long range transmission of conformational effects. The significant differences between these conformers are reflected i n the disposition of the 4 -0H (Figure 7a) when the inner ring i s used as the common structural feature or i n the displacement of the inner phenyl ring and side chain (Figure 7b) when the outer ring i s used as the common feature. Depending on the receptor-site binding requirements, these differences may be directly linked to variations in receptor binding a f f i n i t y and hormone activity. 1

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch013

1

f

Hydrogen Bonding An analysis of the hydrogen bonding and molecular packing of the thyroactive compounds i n their crystal l a t t i c e offers an insight into the molecular details of hydrogen bond strength and directionality at the hormone-receptor s i t e . In the thyronine nucleus (1) the amine acts as a hydrogen bond donor, (2) the carboxylic acid group acts as a hydrogen bond acceptor, and (3) the 4 -0H can act both as a hydrogen bond donor and acceptor, depending on i t s environment. A study of the hydrogen bonding observed i n these crystal structures (11) shows that there i s a high degree of directional s p e c i f i c i t y i n the location of hydro­ gen bond donors and acceptors. In those structures where the 4 -OH acts as a hydrogen bond donor (Table I, Figures 8 and 9), the acceptor atom i s a carbox­ y l i c oxygen from an adjacent molecule i n the l a t t i c e . The acceptor atoms approach the 4'-OH from directions nearly coplanar with the phenoxy ring plane (C3 -C4 -04 1...X) and at an angle (C4 -04 1...X) of 120°. In addition, for T structures, the direction of approach i s trans to the 3 -iodine, whether d i s t a l or proximal. When the 4'-OH acts as a hydrogen bond acceptor, the donor atoms (Table I) tend to approach the phenoxy ring from directions either above or below the plane and opposing the f

f

,

f

,

t

,

3

1

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

CODY

Thyroid Hormones-Receptor Interactions

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch013

13.

Figure 7. Superposition of a skewed (dark) diphenyl ether conformation on a twist-skewed (light) conformation, (a) Overlap of inner ring as common structural feature and (h) the outer phenyl ring.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

2.59 2.82

119 118

162 -177

08 010

f

2

acid

2

3 -isopropyl-diiodothyronine H 0 (25)

1

2 ,3 -dimethyl-diiodothyronine H 0 (24)

1

triiodothyropropionic ethyl ester (23)

triiodothyronine, HC£, H 0 (22)

09

160

115

2.75

2.63

124

151

09

triiodothyronine (13)

2

2.59

119

-176

09

triiodothyroacetic acid (19)

triiodothyronine methyl ester (14)

diiodothyropropionic acid (21)

acid (11)

dibromothyroacetic

2.972 2.04 124° 116

38° -77

N4 N8

2.62&

108°

-175°

09

0...X

f

X

,

0...X

01 01

-83 -6

127 127

2.51 2.73

3.17 2.51

2.68 2.69 127 119 108 176 02 03

113 137

2.82 151 -10 N8

-94 49

3.02 145 33 07

01 02

2.69 126 168

N8

f

C4 -04 l ...X

f

f

4 -OH as Acceptor C3 -C4 04'1...X

diiodothyronine (20)

,

X

Structure

I

C4 -04 1 .. .X

f

!

f

C3 -C4 04 1...X

f

4 -0H as Donor

Hydrogen Bond Directionality i n Thyroactive Structures

Table I

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch013

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

2.71 2.70 2.65 2.60 2.65 2.70

132 118 113 134 113 130

89 -78 73 -102 73 109

N4* N4**

thyroxine (11)

N8 N44 N8* N43

A

Β

tetraiodothyroformic acid

(υ)

2.59

3.08

108

150

118

178

09

04Ί 07*

tetraiodothyroacetic acid (19)

C3'-C4'04Ί...Χ

X

2.91

0...X 145

C4'-04'l ...X -25

thyroxine, HC£, H 0 (22)

2

C3'-C4'04Ί...Χ

0. ..:

Χ

4'-OH as acceptor C4'-04'l .. .X

Structure

4 -0H as Donor

f

Table I. (Continued)

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch013

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch013

Figure 8. Example of the direction of approach of (a) hydrogen bond acceptor to the 4'-OH of T ; (b) hydrogen bond donor and acceptor to the 4''-hydroxyl of T ; and (c) hydrogen bond donors to the 4'-phenoxide of Τ\ 3

3

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

CODY

Thyroid Hormones-Receptor Interactions

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13.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

291

COMPUTER-ASSISTED DRUG DESIGN

292

acceptor atom (Figure 8b). As seen from Table I, the average value for the hydrogen bond angle C4-04 1...X i s 116° when the 4 -0H acts as a donor and 129° when i t i s an acceptor. Also, when the 4 -0H i s simulta­ neously involved as a donor and acceptor, the donor atom to 4 -0H tends to have an angle near 150°. In those situations where the hydrogen bonding atoms are water, one adopts the orientation observed for the carboxylic oxygens, suggesting that i t i s a hydrogen bond acceptor from the 4 -0H. In the case of tetraiodothyroactive structures where the 4'-oxygen i s a phenoxide ion (11) and thus only a hydrogen bond acceptor, the donor atoms approach the 4*-phenoxy ring symmetri­ cally from directions both above and below the plane (Figure 8c). However, where the tetraiodo structures are hydroxyIs (T^A (19)), the outer ring iodines cause the approach of the donor/acceptor atoms to deviate from this pattern. A study of the 4 -0...X hydrogen bonds i n these structures shows that the average 0...0 distance i s 2.74$ and the 0...N distance i s in general agreement with other studies (26). When the donor and acceptor 0...0 values are considered sepa­ rately, these become 2.668 and 2.8l8 for 4 -0H as a donor and acceptor, respectively. The results of theoretical energy calculations of interand intramolecular hydrogen bond strengths of ortho substituted phenols and phenoxides (27), as models to investigate l i k e l y orientations of thyroid hormones at their protein binding sites, are i n general agreement with the hydrogen bonding patterns observed in these crystallographic determinations. These energy calculations predict an average 0...0 distance of 2. 63X and a C-0...0 angle of 125°, irrespective of whether the 4 -0H i s acting as a proton donor or acceptor. Unfortunately, this study (27) did not compute the hydrogen bond geometry when the 4 -0H is simultaneously acting as a hydrogen bond donor and acceptor and consequently the detail observed from the crystallographic data i s not apparent. The observation that i n the 3 -substituted structures the hydrogen bonding atom approaches the 4 -0H trans to the 3'-sub­ stituent i s verification of quantitative structure activity relationship (QSAR) data which also suggest that in vitro binding of Τ3 probably involves hydrogen bond donation of the 4 -0H to the 5'-side of the nuclear receptor (28). ?

f

f

?

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch013

f

f

f

f

f

1

f

f

Protein Binding Characteristics Because thyroid hormones are protein boun^i throughout the general circulation as well as i n the c e l l membranes and nucleus, protein binding is central to the transport, tissue distribution and metabolism rates of the various thyroid analogues (29). Current theory proposes that the hormone f i r s t binds at a spe­ c i f i c site on the protein receptor and then an interaction

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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293

between the hormone and a complementary receptor component takes place. Steric correspondence between the receptor site and the hormone then permits electronic interaction. Thus, the struc­ tural s p e c i f i c i t y of the hormones can be both steric and elec­ tronic i n nature. The importance of specific structural features in binding to the various thyroid binding proteins has been suggested from numerous studies measuring the relative binding a f f i n i t i e s of the hormones and their analogues for these serum, nuclear and membrane proteins (30-36). These studies indicate that the binding site requirements are different for each of the proteins. Table II l i s t s a few of the activity and binding a f f i n i t y data available for the thyroid hormones and their analogues to membrane, serum and nuclear proteins (11). Structural require­ ments for potency correlate closely with those for in vitro binding to nuclear proteins (37). These correlations, i n con­ junction with other thyroid hormone studies, provide a general description of the structural features required for binding and hormonal activity (Table I I I ) . As illustrated, the major binding requirements d i f f e r principally with regard to the 3 ,4 ,5'-sub­ stituents. The nuclear receptors preferentially bind to d i s t a l l y 3'-oriented compounds, as do the membrane bound proteins, while the serum proteins have maximal binding for 3 ,5'-disubstituted compounds with electron withdrawing groups. Also, from pH depen­ dency studies of T and T binding, i t i s apparent that 4 -0H binds to the nuclear receptors i n i t s un-ionized form whereas i t binds to the serum protein receptors i n i t s ionized form (28,30). These results correlate well with the crystallographic observa­ tions of structures as 4'-phenoxide ions and T as un-ionized 4'-hydroxyls. f

f

1

f

3

4

3

Receptor Models Recent crystallographic studies of thyroxine-binding pre­ albumin (38,39,40) show i t to be a tetramer with a channel running through the structure. The four units are related by two perpendicular 2-fold axes. Complexes of TBPA with Ti+ and Τ3 show the hormones are bound inside the channel (Figure 10) with the 4'-phenoxy ring pointed toward the center of the core. However, because the thyroid hormones cannot be accommodated by the symmetry requirements of the protein, their exact orientation in the receptor s i t e cannot be defined. Instead, an average position of two symmetry related orientations i s observed. Nevertheless, this description of TBPA structural features, com­ bined with relative binding a f f i n i t y data (41) of analogues to TBPA, permits a detailed model of the hormoiie-receptor inter­ action to be formulated. In this case, the 4'-phenoxy ring i s tightly bound, v i a hydrogen bonds, to a water or peptide func­ tional group (39) suggesting that 4'-0H interactions are a primary requirement for binding. I f , on the other hand, the side

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

!

3

3

3

4

1

f

1

1

L-thyroxine (Ti+) D-thyroxine tetraiodothyropropionic acid (T P) tetraiodothyroacetic acid (Ti+A) tetraiodothyroformic acid (Ti+F) te trabromo-DL-thyr onine tetramethy1thyronine 2 ,3 -dimethyl-3,5-diiodo thyronine 2',5 -dimethy1-3,5-diiodothyronine 3,5,3'-triiodo-L-thyronine (T ) 3 ,5 ,3-triiodothyronine (RT ) triiodothyroacetic aeid (T A) tr ime thy1thyronine

Compound 39.3% .95 76.4 100.0 90,2

1.4 3.1 4.7

-

100.0% 54.0 3.6 1.7 40.0 0.0 0.71 0.13 9.0 38.0 0.3

-

-

TBPA (41)

TBG (33)

0.1

-

1.1 0.1 100.0 0.1

—

67.5 60.6

100.0

-

0.3 6.3 0.1 100.0 best binder

1

f

3

Membrane

appears to be similar to the nuclear proteins

A l l proteins require a diiododiphenyl ether nucleus. The implications of these data are that TBG and nuclear proteins prefer a twist-skewed diphenyl ether conformation whereas TBPA prefers a skewed diphenyl ether.

chain orientation and composition were of primary importance, as suggested from TBG and nuclear protein data (30,31,32,33), then the consequences of changes i n the side chain orientation (χ , χ , Figure 4) would be significant. The most striking feature of the data l i s t e d i n Table II i s that the acid metabolites bind more strongly to TBPA than thyrox­ ine; just the opposite of the order observed for TBG and the nuclear proteins. A factor which may influence these parameters is the relative importance to binding of the diphenyl ether con­ formation and the side chain conformation. As was shown (19), the thyroactive acid structures prefer a skewed diphenyl confor­ mation whereas the thyronine structures adopt a twist-skewed con­ formation. As illustrated (Figure 7), there i s significant dis­ placement of the 4'-OH and side chain functional groups between these two conformers. Therefore, i f 4'-phenoxy interactions control binding, these differences w i l l affect the position of the side chain groups within the binding channel. When the molecular structures of the acid metabolites T A (dark, Figure 11) i s successively superimposed over that of (a) Ti+F, (b) Ti+P, (c) T , and (d) a l l of them; i t can be seen that the acid side chains describe a probably binding volume from which the T4. amine i s excluded. In addition, the Ti+ inner ring has the largest deviation from the positional range described by the acid metabolites. Also, the carboxylic oxygens of the various metabolites (except T 4 F ) , irrespective of composition, 1

2

4

4

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch013

Figure 11. Superposition of molecular structure of T A with (a) T F; (b) T^P; (c) T\; and (d) all of them, illustrating binding volume of thyroactive acid metabolites, assuming 4'-phenoxy ring fixed. h

If

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Hormones—Receptor

Interactions

297

tend to cluster together, suggesting that this feature may also be of importance i n determining relative binding a f f i n i t y . Analysis of the TBPA-T^ complex (39,40) indicates that the binding site for the hormone i s located deep inside the channel. The hormone makes extensive interactions with the protein side chains that project into the channel. The 4'-hydroxy1 of T^ interacts with a patch of hydroxy-amino acids of the protein while each of the iodines makes contact with a number of hydro­ phobic protein residues. The Ti+ amino acid side chain functional groups are i n appropriate positions to interact with glutamic acid and lysine residues. Thus, this channel provides a favorable environment for each of the characteristic substituents of the thyroid hormone (40) . However, because of the Ti+ orientation disorder i n the protein complex, this structural model i s not a sensitive measure of the observed correlations between diphenyl ether conformations and binding a f f i n i t y data. The differences i n binding orders between TBPA and TBG suggest that different structural features may play a key role in receptor interactions. I t has been shown (4,28) that TBG also preferentially binds to a tetraiodo-4 -phenoxide ion, but since Τΐψ i s the strongest binder, this suggests a different side chain stereochemistry. Here we can assume that i t i s the twist-skewed diphenyl ether conformation which orients the Ti+ side chain for optimal receptor-hormone interactions. In the case of the nuclear proteins optimal binding i s observed for a d i s t a l l y oriented 3 -I and a 4 -hydroxyl. Side chain requirements appear to be similar to those of TBG (28,31). Therefore, changes i n the relative binding a f f i n i t i e s of thyroid hormone structures to receptors w i l l ultimately depend upon the specific steric requirements of the binding site and the a b i l i t y of the hormones to adopt the required conformation. In addition, the net charge of the hormone could also influence i t s binding a b i l i t y . Thus, the observation of conformational patterns among thyroactive structures which correlate with function, activity and binding data provide useful information in describing specific types of hormone-receptor interactions. T

!

f

Acknowledgements This research was supported i n part by a grant from HEW AM-15051. Graphs and figures were prepared through interro­ gation of the thyroid data stored i n the NIH PROPHET system, an NIH interactive computer network. The secretarial and technical assistance of Mrs. B. Giacchi, Miss M. Tugac, Miss G. Del Bel and Mrs. C. DeVine are gratefully acknowledged.

Literature Cited 1.

Zenker, N.; Jorgensen, E. C. J . Amer. Chem. Soc., 1959, 4643.

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81,

298 2.

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3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32.

COMPUTER-ASSISTED DRUG DESIGN

Oppenheimer, J . H . ; Schwartz, H. L.; Surks, M. I.; Koerner, D.; Dillman, W. H. Recent Progr. Horm. Res., 1976, 32, 529. Lehmann, P. A. J. Med. Chem., 1972, 15, 404. Jorgensen, E. C. Pharmac. Ther., 1976, B2, 661. Jorgensen, E. C.; Lehmann, P. Α.; Greenberg, C.; Zenker, N. J . Biol. Chem., 1962, 237, 3832. Jorgensen, E. C. Mayo Clinic Proc., 1964, 39, 560. Schussler, G. C. Science, 1972, 178, 172. Lehmann, P. Α.; Jorgensen, E. C. Tetrahedron, 1965, 21, 363. Kier, L. B.; Hoyland, J. R. J. Med. Chem., 1970, 13, 1182. Camerman, N.; Camerman, A. Science, 1972, 175, 764. Cody, V. Recent Progr. Horm. Res., 1978, 34, 437. Cody, V. Science, 1973, 181, 757. Cody, V. J. Amer. Chem. Soc., 1974, 96, 6720. Cody, V. J . Med. Chem., 1975, 18, 126. Cody, V.; Duax, W.L. Biochem. Biophys. Res. Comm., 1973, 52, 430. Emmett, J . C.; Pepper, E. S. Nature, 1975, 257, 334. Kollman, P. Α.; Murray, W. J.; Nuss, M. E.; Jorgensen, E. C.; Rothenberg, S. J . Amer. Chem. Soc., 1973, 95, 8518. Cody, V.; Duax, W. L.; Hauptman, H. A. Int. J . Peptide Protein Res., 1973, 5, 297. Cody, V.; Hazel, J . P.; Langs, D. Α.; Duax, W. L. J. Med. Chem., 1977, 20, 1628. Cody, V.; Duax, W. L.; Norton, D. A. Acta Cryst., 1972, B28, 2244. Cody, V.; Erman, M.; DeJarnette, F. E. J. Chem. Res., 1977, S, 126. Camerman, Α.; Camerman, N. Acta Cryst., 1974, B30, 1832. Camerman, N.; Camerman, A. Can. J. Chem., 1974, 52, 3048. Fawcett, J . K.; Camerman, N.; Camerman, A. Can. J. Chem., 54, 1317. Fawcett, J . K.; Camerman, N.; Camerman, A. J . Amer. Chem. Soc., 1976, 98, 587. Mitra, J.; Ramakrishnan, C. Int. J . Peptide Protein Res., 1977, 9, 27. Andrea, Τ. Α.; Dietrich, S. W.; Murray, W. J.; Kollman, P. Α.; Jorgensen, E. C.; Rothenberg, S. J . Med. Chem., 1979, 22, 221. Dietrich, S. W.; Bolger, M. B.; Kollman, P. Α.; Jorgensen, E. C. J . Med. Chem., 1977, 20, 863. Pittman, C. S.; Pittman, J . A. In:"Physiology, Vol. III, Thyroid", Greer, Μ. Α.; Solomon, D. H . , Ed.; American Physiological Society: Washington, D.C., 1974. Tabachnick, M.; Korcek, L. Biochimica et Biophysica Acta, 1978, 537, 169. Koerner, D.; Schwartz, H. L.; Surks, M. I.; Oppenheimer, J . H.; Jorgensen, E. C. J. Biol. Chem., 1975, 250, 6417. Goldfine, I. D.; Smith, G. J.; Simons, C. G.; Ingbar, S. H.; Jorgensen, E. C. J. Biol. Chem., 1976, 251, 4233.

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13. 33. 34. 35. 36. 37.

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38. 39. 40. 41.

Cody

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299

Snyder, C. M.; Cavalieri, R. R.; Goldfine, I. D.; Ingbar, S. H.; Jorgensen, E. C. J. Biol. Chem., 1976, 251, 6489. Spindler, B. J.; MacLeod, Κ. M.; Ring, J.; Baxter, J . D. J . Biol. Chem., 1975, 250, 4113. Singh, S. P.; Carter, A. C.; Kydd, D. M.; Costanzo, R. R. Endocrine Res. Comm., 1976, 3, 119. Sterling, K.; Milch, P. O.; Brenner, Μ. Α.; Lazarus, J. H. Science, 1977, 197, 996. Jorgensen, E. C. In: "The Thyroid", Werner, S. C.; Ingbar, S. H., Ed.; Harker & Row, 1978; p. 125. Blake, C. C. F.; Geisow, M. J.; Swan, I. D. Α.; Rerat, C.; Rerat, B. J . Mol. Biol., 1974, 88, 1. Blake, C. C. F . ; Oatley, S. J . Nature, 1977, 268, 115. Blake, C. C. F. Endeavour, 1978, 2, 137. Andrea, T. A. Ph.D. Thesis, 1977, University of California, San Francisco.

Received June 8, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

14 Theoretical Modeling of Enzymic Hydrolysis of Acetylcholine Compared to Acetylthiocholine JOYCE H . CORRINGTON

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch014

Xavier University of Louisiana, New Orleans, L A 70125

Acetylcholine (ACh, 51-84-3) is a molecular ion which functions as a neurohumoral transmitter in the peripheral nervous system. It is released at the end of one cell, diffuses across the synapse, induces permeability changes in the next cell, and is then rapidly removed from the synaptic region by a hydrolytic reaction catalyzed by the enzyme acetylcholinesterase (AChE, EC 3 . 1 . 1 . 7 ) . Replacement of the acetate oxygen of ACh by sulfur y i e l d i n g the thiol ester analog a c e t y l t h i o choline (ASCh, 4468-05-7) profoundly modifies the b i o l o g i c a l action of this molecular ion ( 1 , 2 , 3 ) . The r e l a t i v e a b i l i t y of these isosteres to induce p o l a r i z a tion in isolated single c e l l electroplax preparations is 1.0:16.7 (4). However, the r e l a t i v e rate at which these isosteres are hydrolyzed by AChE is very s i m i l a r , 1.0:0.6 (5). Proposals made concerning this hydrolysis mechanism suggest that the active s i t e of AChE consists of a nucleophilic serine residue and a h i s t i d i n e residue which probably serves as a proton donor or receiver (6). Hydrolysis is thought to occur through the formation of a Michealis complex between the active s i t e of the AChE and the substrate (S), the conversion of the complex in an "acylation" reaction to an acyl enzyme intermediate (AChE•A) and the product choline (or t h i o c h o l i n e ) , and the subsequent hydrolysis of the acyl enzyme in a "deacylation" reaction to acetic acid and the regenerated enzyme ( 7 , 8 , 9 ) .

The a c y l a t i o n

reaction

appears

controlled

by a f u n c t i o n a l

0-8412-0521-3/79/47-112-301$05.00/0 © 1979 American Chemical Society

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302

COMPUTER-ASSISTED DRUG DESIGN

g r o u p o f p K = 5.3, w h i l e t h e d e a c y l a t i o n r e a c t i o n a p p e a r s c a t a l y z e d b y a g r o u p o f p K = 6.3, a n d f o r b o t h A C h a n d ASCh t h er a t e d e t e r m i n i n g s t e p i s t h ed e a c y l a t i o n reac­ t i o n (10J. Semiempirical m o l e c u l a r o r b i t a l c a l c u l a t i o n s have b e e n e m p l o y e d t o c o m p a r e t h e c o n f o r m a t i o n [11) a n d t h e e l e c t r o n i c p r o p e r t i e s o f A C h a n d A S C h (1_2). T w o s t u d i e s have i n v e s t i g a t e d proposed h y d r o l y s i s mechanisms f o r ACh (1_3,1_4). T h i s s t u d y s i m i l a r l y e m p l o y s semiempirical c a l c u l a t i o n s t o i n v e s t i g a t e t h ecommonly p r o p o s e d steps o f the mechanism f o r the AChE c a t a l y z e d h y d r o l y s i s o f ACh a n d A S C h . In t h i s s t u d y t h e m o l e c u l a r o r b i t a l c a l c u l a t i o n p r o g r a m e m p l o y e d , ARCANA, u t i l i z e d o n l y a t o m i c d a t a a n d i t e r a t e d t o charge s e l f - c o n s i s t e n c y (see Cal c u l a t i o n Note). T h e s u b s t r a t e s , ACh a n d ASCh, and t h e products of hydrolysis, choline, thiocholine, and acetic acid, were r e p r e s e n t e d i n t h e i r e n t i r e t y , w h i l e the AChE e n z y m i c a c t i v e s i t e was m o d e l e d b yr e p r e s e n t i n g t h e h i s t i d i n e r e s i d u e a n d t h es e r i n e residue thought t o be at t h ea c t i v e s i t e b yimidazol a n d methanol r e s p e c t i v e l y . M o l e c u l a r o r b i t a l c a l c u l a t i o n s have been p e r f o r m e d f o r reactants, three possible intermediate a c y l a t i o n com­ p l e x e s , and t h ea c y l a t i o n products. Since the deacyla­ t i o n mechanism i s i d e n t i c a l f o r both ACh a n d ASCh a n d has been r e p o r t e d e l s e w h e r e ( 1 4 ) , t h o s e r e s u l t s w i l l not ber e p e a t e d here. F o r eacTT o f t h e a c y l a t i o n steps, three cases were c a l c u l a t e d : ( a ) general acid catalyzed, (b) n o n - c a t a l y z e d o r n e u t r a l , a n d (c) general base c a t a ­ lyzed. Molecular orbital coefficients and energies, t o t a l valence e n e r g i e s , Mulliken n e tatomic charges, bond a n d t o t a l o v e r l a p p o p u l a t i o n s , a n d bond a n d t o t a l o v e r l a p energies were c a l c u l a t e d f o r each run. The a t o m i c c o o r d i n a t e s used f o r ACh were those e m p l o y e d i n a p r e v i o u s t h e o r e t i c a l s t u d y (15J a n d w e r e calculated employing i d e a l i z e d hybridization and average bond d i s t a n c e s . While c r y s t a l l o g r a p h i c s t u d i e s o f ACh are a v a i l a b l e ( 1£,Γ7), the gauche c r y s t a l c o n f o r m a t i o n o f ACh was n o tused f o r t h i s s t u d y , b u t r a t h e r an a n t i planar conformation s i m i l a r t o t h et r a n s i t i o n state g e o m e t r y s u g g e s t e d b y k i n e t i c d a t a (TJB-22J . T h e a t o m i c coordinates f o r ASCh i n i t s a n t i - p l a n a r c r y s t a l s t r u c t u r e w e r e e m p l o y e d (23). T h e ASCh c r y s t a l l o g r a p h i c bond d i s t a n c e s a n d the ACh g e n e r a l i z e d bond d i s t a n c e s were i d e n t i c a l w i t h i n 0.04 A , t h e a c c u r a c y o f t h e c r y s t a l l o ­ graphic data, with t h e exception o f those involving sulfur. T a b l e I presents t h ebond d i s t a n c e s employed in these c a l c u l a t i o n s f o r t h e s u b s t r a t e , e i t h e r ACh o r ASCh.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

14. coRRiNGTON

Enzymic Hydrolysis of Acetylcholine

303

Table I Interatomic

Distances

(8)

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch014

X =

X =

1.42

1.97

1.31

1.77

1.23

1.23

1.52

1.52

0.96

1.33

1.09

1.09

1.48

1.48

The i m i d a z o l c o o r d i n a t e s were t a k e n from a n x - r a y d i f f r a c t i o n c r y s t a l l o g r a p h i c study of histamine (24) with a proton being s u b s t i t u t e d f o r the ethylamine s i d e chain of histamine. The c o o r d i n a t e s o f o t h e r r e a c t a n t s , p r o d u c t s , and i n t e r m e d i a t e c o m p l e x e s were c a l c u l a t e d e m p l o y i n g i d e a l i z e d h y b r i d i z a t i o n and a v e r a g e bond distances o rare as d i s c u s s e d . Results the

T h e a c y l a t i o n m e c h a n i s m was four steps following:

assumed

t oc o n s i s to f

Step I. The r e a c t a n t s (ACh o r A S C h , m e t h a n o l , i m i d a z o l ( s ) and/or i m i d a z o l i u m ( s ) form a " p l a n a r " i n t e r mediate complex between the carbonyl carbon of the s u b s t r a t e (which i s in an s p " p l a n a r " h y b r i d i z a t i o n s t a t e ) and t h e o x y g e n o f t h e a t t a c k i n g n u c l e o p h i l e methanol. The n u c l e o p h i l e i s assumed t o a t t a c k p e r p e n d i c u l a r to the plane of the s u b s t r a t e a c e t a t e (or t h i o a c e t a t e ) moity with the e l e c t r o n s from the methanol oxygen f i l l i n g the lowest empty m o l e c u l a r o r b i t a l which is centered on the carbonyl carbon of the s u b s t r a t e . Step moity of with the zatioa of to s p .

I I . The " p l a n a r " a c e t a t e ( o r t h i o a c e t a t e t h e ACh ( o r ASCh) f o r m s a " t e t r a h e d r a l " c o m p l e x a t t a c k i n g n u c l e o p h i l e methanol as the h y b r i d i the s u b s t r a t e carbonyl carbon changes from s p

Step I I I . A "protonated formed by the t r a n s f e r of the

ester" intermediate hydroxy proton from

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

is the

2

304

COMPUTER-ASSISTED DRUG DESIGN

a t t a c k i n g n u c l e o p h i l e methanol t o the acetate oxygen (or t h i o a c e t a t e s u l f u r ) , except i n the base c a t a l y z e d pathway where t h i s p r o t o n h a s a l r e a d y been donated t o an i m i d a z o l , a n d t h i s s t e p i s n o t a s s u m e d .

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch014

Step IV. The "protonated ester" intermediate breaks i n t o c h o l i n e (or t h i o c h o l i n e ) a n d an a c y l enzyme i n t e r m e d i a t e , modeled here by methyl acetate. Each o f the above s t e p s was c a l c u l a t e d f o r t h r e e pathways: (a) assuming an i m i d a z o l i u m p r e s e n t a t the AChE a c t i v e s i t e a c t e d a s a g e n e r a l a c i d c a t a l y s t a n d donated a proton t o the a c y l oxygen o f the s u b s t r a t e (thus two i m i d a z o l s were i n c l u d e d i n the c a l c u l a t i o n s ) , (b) a s s u m i n g t h e r e was no a c i d o r base c a t a l y s t ( t h u s one i m i d a z o l a n d o n e i m i d a z o l i u m were i n c l u d e d i n t h e c a l c u l a t i o n s ) , a n d (c) assuming an i m i d a z o l present at the AChE a c t i v e s i t e a c t e d a s a g e n e r a l base c a t a l y s t and a b s t r a c t e d a p r o t o n from t h e n u c l e o p h i l e m a k i n g i t a methoxy (thus two imidazoliums were i n c l u d e d i n t h e calculations). I n a l l cases the number o f atoms p r e s e n t were thus kept c o n s t a n t from run t o run. S i n c e no c r y s t a l l o g r a p h i c data o f the a c t i v e s i t e are a v a i l a b l e , modeling o f the s p e c i f i c i n t e r a c t i o n o f the h i s t i d i n e residue with the proposed r e a c t i o n intermediate complexes was n o t a t t e m p t e d . While a f e w angles a n d d i s t a n c e s were v a r i e d d u r i n g the modeling, i ngeneral these were not optimized. T h ed i s t a n c e between the s u b s t r a t e carbonyl carbon andthe n u c l e o p h i l i c oxygen i nthe " p l a n a r " i n t e r m e d i a t e complex was s e l e c t e d so t h a t the c o o r d i n a t e s of the n u c l e o p h i l e d i d not have t o be a l t e r e d as t h e s u b s t r a t e changed h y b r i d i z a t i o n and formed the " t e t r a h e d r a l " i n t e r m e d i a t e complex with a normal carbon t o oxygen bond d i s t a n c e . Discussion Total Valence Energy. Thecalculated total valence e n e r g i e s presented below i nTable I I are the e q u i v a l e n t of t o t a l e n e r g i e s but i n c l u d e o n l y f a c t o r s d u e t o the valence e l e c t r o n s and the nuclear charges corresponding to them. A l l runs were converged t o a 1 kcal/mole t o l e r a n c e , but s i n c e a r b i t r a r y a n d r i g i d conformations were employed these e n e r g i e s should be taken o n l y as i n d i c a t i v e o f the energy changes i n v o l v e d . A l s o , o f course, entropy and s o l v a t i o n e f f e c t s are not included i n such i s o l a t e d o r "gas p h a s e " m o l e c u l a r c a l c u l a t i o n s . But even w i t h t h e s e q u a l i f i c a t i o n s , the t o t a l v a l e n c e e n e r g i e s i n d i c a t e t h a t both ACh a n d ASCh would f o l l o w a l o w e r e n e r g y a c y l a t i o n p a t h w a y when a c i d c a t a l y z e d (when

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Enzymic Hydrolysis of Acetylcholine

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch014

14. coRRiNGTON

305

Table I I Total Valence Energy f o r Steps i n the Enzymic A c y l a t i o n o f ACh and ASCh ( g - k c a l / m o l e , r e l a t i v e t o t h e r e a c t a n t s ) M e c h a n i sm Step

(A) A c i d Catalyzed

(B) NonCatalyzed

(C) Base Catalyzed

S u b s t r a t e : ACh

ASCh

ACh

ASCh

ACh

ASCh

I II III IV

25 15 -58

162 96 138 57

153 110 120 79

315 283

293 274

-12 -63 -47

-

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306

COMPUTER-ASSISTED DRUG DESIGN

the i m i d a z o l i u m assumed present a t the c a t a l y s t ' s a c t i v e s i t e donates a proton t o the acyl oxygen o f the substrate). T h e energies o f the ACh "planar" and" t e t r a h e d r a l " i n t e r m e d i a t e complexes are lower than those f o r ASCh. Both the A C h a n d the ASCh " t e t r a h e d r a l " i n t e r m e d i a t e s are lower i nenergy than the corresponding "planar" i n t e r m e d i a t e s , as might be expected. A notica b l e d i f f e r e n c e e x i s t s i n t h e i n t e r m e d i a t e f o r m e d when a proton i s s h i f t e d from the a t t a c k i n g n u c l e o p h i l e t o the acetate oxygen (or t h i o a c e t a t e s u l f u r ) , s i n c e the ACh i n t e r m e d i a t e i s n o t a s s t a b l e a s i t s " t e t r a h e d r a l " i n t e r m e d i a t e , w h i l e the ASCh i n t e r m e d i a t e i s c o n s i d e r a b l y more s t a b l e than i t s " t e t r a h e d r a l " i n t e r m e d i a t e a n d indeed roughly e q u i v a l e n t t o the ACh " t e t r a h e d r a l " intermediate. These ACh a n d ASCh i n t e r m e d i a t e s are both more s t a b l e than the proposed a c y l a t i o n p r o d u c t s c h o l i n e (or t h i o c h o l i n e ) a n d the a c y l enzyme (modeled here by methyl a c e t a t e ) . In both cases the a c y l a t i o n r e a c t i o n is c a l c u l a t e d t o be endothermic. S i n c e the r e s u l t i n g a c y l enzyme i s i d e n t i c a l f o r both s u b s t r a t e s , the d e a c y l a t i o n r e a c t i o n would be i d e n t i c a l f o r both and i s not d i s c u s s e d here. However, a s i m i l a r p r e v i o u s s t u d y (1_4) d i d i n d i c a t e t h a t d e a c y l a t i o n would have t o procedle t h r o u g h a h i g h e r e n e r g y pathway than e i t h e r the A C h o r the ASCh a c y l a t i o n , a n d thus would be r a t e l i m i t i n g as experimental data suggests (10). M u l l i k e n Net A t o m i c C h a r g e s . Thenet atomic charges calculated according t o a Mulliken population analysis (25) are p r e s e n t e d below i nT a b l e I I I f o r the l o w e n e r g y or general a c i d c a t a l y z e d pathway. Both ACh a n d ASCh are molecular ions with p o s i t i v e l y charged c a t i o n i c "heads." T h e c a l c u l a t e d t o t a l M u l l i k e n net atomic c h a r g e s on the onium m e t h y l s o f both ACh a n d ASCh t o t a l approximately 0.98and s t a y e s s e n t a i l l y constant throughout the proposed mechanism steps. S i m i l a r l y , the net charge on the onium n i t r o g e n i si n i t i a l l y a negative -0.31 ( i n c o n t r a s t t o common n o t a t i o n w h i c h d e n o t e s t h e nitrogen as p o s i t i v e l y charged). The n i t r o g e n net charge becomes somewhat l e s s n e g a t i v e i n the proposed mechanism s t e p s , but net charges i nthe t o t a l onium f u n c t i o n a l g r o u p s i nACh, ASCh, c h o l i n e a n d t h i o c h o l i n e s t a y essentailly constant and equivalent. The c a r b o n y l o x y g e n i s t h e most n e g a t i v e atom i n both s u b s t r a t e s , a n d h a s a M u l l i k e n net charge o f -0.698 in ACh a n d -0.661 i nASCh. Centered on i t i nboth subs t r a t e s i s the highest occupied molecular o r b i t a l , thus the c a r b o n y l oxygen i s the most s u b j e c t t o e l e c t r o p h i 1 i c attack or protonation. In the intermediated formed i n

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

I V

τ TA ιπ ι

2

0.,364 0.,396 0,.447 0..439 0,. 3 6 3

0,,306 0,.361 0,. 4 3 4 0..395 0,.410

- 0 .,670 - 0 ..492 - 0 ,,348 - 0 ..625 -0,. 6 6 2

0..877 0,,958 0,.932 0,.907 0 .895

. „ ^ c (

-0. -0. -0. -0. -0.

-

698 5 2 9 0,.376 5 9 3 0,.341 5 9 3 0,.357 712

+

0.100

0. 101 Q. 1 3 6 0. 0 7 4 0. 0 9 0 0. 0 6 9

3

===== 0 - " H ) - ( C H )

0.118 0.364 0.306 -Q.670 0.438 -0.661

- 0 .,612 - 0 ..558 - 0 , .606 - 0 , .379 - 0 .. 6 1 4

- X

I n t e r m e d i a t e s f o r S u b s t r a t e s ACh and ASCh

0.962 -0.268 0.308 0.067 0.429 0.469 - 0 . 3 6 6 0.551 -0.58Q 0.351 0.077 0 979 -0.251 0.394 0 . 5 4 2 0.1 51 0 . 3 7 0 - 0 . 6 4 6 0 . 5 9 7 - 0 . 5 9 1 0 . 3 6 8 0 . 0 8 8 (K972 -0.310 Q.242 -0.021 0.067 0.410 -0.662 0.895 -0.712 0.069

0.976 -0.308 0.334

Methanol

0,,669 0..644 0,.625 0..679 0,. 5 9 4

2

-(CH )

ASCh

- 0 .,314 - 0 .,266 - 0 .,269 - 0 ..252 - 0 ,.316

+

for Acylation

0..986 0..966 0.. 9 6 4 0..981 0,.972

- N

Charges

Reactants ACh, Methanol IA 11A 111A IV

3

(H C)

Mechanism Step

3

Net Atomic

Mulliken

Table III

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COMPUTER-ASSISTED DRUG DESIGN

the a c i d c a t a l y z e d pathway, t h i s oxygen i sassumed t o be protonated by a proton donated by an imidazolium a t the AChE's a c t i v e s i t e . The M u l l i k e n net charge o f t h i s o x y g e n becomes s l i g h t l y l e s s n e g a t i v e when p r o t o n a t e d , but i s s i m i l a r whether the s u b s t r a t e i s ACh o r ASCh. The p r o t o n r e t a i n s o n l y a f r a c t i o n o f i t s n e t p o s i t i v e c h a r g e , v a r y i n g f r o m 0.341 t o 0.382 among t h e proposed intermediates. I t thus apparently withdraws c o n s i d e r a b l e e l e c t r o n d e n s i t y , but not from the a d j a c e n t a c y l oxygen, r a t h e r from the oxygen o f the a t t a c k i n g n u c l e o p h i l e , thus h e l p i n g s t a b i l i z e the d e v e l o p i n g bond between the s u b s t r a t e and the a t t a c k i n g n u c l e o p h i l e . The c a r b o n y l c a r b o n i s t h e most p o s i t i v e atom i n both s u b s t r a t e s , but i sc o n s i d e r a b l y more p o s i t i v e i n the ACh (0.877) than i n the ASCh (0.438). However,t h e lowest energy empty m o l e c u l a r o r b i t a l (LEM0), which i s c e n t e r e d on t h i s atom p e r p e n d i c u l a r t o the plane o f the acetate (or t h i o a c e t a t e ) moity, hass i m i l a r o r b i t a l e n e r g i e s f o r both the A C h (-12.00 e V ) a n d the ASCh (-12.35 e V ) . Both the p o s i t i v e M u l l i k e n net atomic c h a r g e a n d t h e l o c a t i o n o f t h e LEMO o n t h e c a r b o n y l c a r b o n make i t s u b j e c t t o n u c l e o p h i l i c a t t a c k . In the i n t e r m e d i a t e s formed i n the proposed a c i d c a t a l y z e d mechanism s t e p s , the M u l l i k e n net atomic charges o f the carbonyl carbon does not change g r e a t l y d e s p i t e the f o r m a t i o n o f the d e v e l o p i n g bond between the s u b s t r a t e and the a t t a c k i n g n u c l e o p h i l e . The a c e t a t e o x y g e n i st h e s e c o n d s i t e o f n e t n e g a t i v e charge i n the ACh s u b s t r a t e (-0.612), but the corresponding t h i o a c e t a t e s u l f u r hasa net p o s i t i v e charge i n the ASCh s u b s t r a t e (+0.118). This difference i n net c h a r g e h a s been p r o p o s e d a s t h e e x p l a n a t i o n why the c r y s t a l s t r u c t u r e o f ACh a n d ASCh a r e d i f f e r e n t ( 1 2 ) . I t may a l s o e x p l a i n why the t o t a l v a l e n c e e n e r g i e s o f the proposed ASCh " p l a n a r " a n d " t e t r a h e d r a l " a c y l a t i o n i n t e r m e d i a t e s are higher than the corresponding ACh intermediates. T h i s a c e t a t e oxygen (and t h i o a c e t a t e s u l f u r ) i s a l s o the primary s i t e o f the second h i g h e s t energy o c c u p i e d m o l e c u l a r o r b i t a l , an a n t i - b o n d i n g pi-type o r b i t a l shared with the carbonyl oxygen. Because o f t h i s , i t was proposed t h a t a p o s s i b l e a c y l a t i o n i n t e r m e d i a t e (111A) c o u l d r e s u l t i f a proton was t r a n s f e r r e d from the hydroxy o f the a t t a c k i n g n u c l e o p h i l e t o the acetate oxygen (or t h i o a c e t a t e s u l f u r ) . This intermediate r e s u l t e d i n a moderate p o s i t i v e change i nthe net atomic charge o f the a c e t a t e oxygen, but a l a r g e p o s i t i v e change i nthe net charge o f the t h i o a c e t a t e s u l f u r . In t h e s e p a r a t e d c h o l i n e m o l e c u l a r i o n , t h e h y d r o x y oxygen r e t u r n s t o a net atomic charge (-0.614) s i m i l a r

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

14.

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t o w h a t i t was i n t h e c h o l i n e m o i t y o f t h e A C h , while in the separated t h i o c h o l i n e m o l e c u l a r ion the mercaptan s u l f u r has a more n e g a t i v e net a t o m i c c h a r g e (-0.021) than i t had i n t h e t h i o c h o l i n e m o i t y o f ASCh.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch014

Bond O v e r l a p P o p u l a t i o n . The c a l c u l a t e d bond o v e r l a p p o p u l a t i o n s f o r some o f t h e b o n d s i n v o l v e d i n the a c y l a t i o n r e a c t i o n are presented below i n Table IV. The o v e r l a p p o p u l a t i o n (OP) b e t w e e n a t o m s A and Β i s c a l c u l a t e d by:

w h e r e i and j a r e summed o v e r a l l a t o m i c b a s i s o r b i t a l s and u o v e r a l l m o l e c u l a r orbitals. I n t h e A C h s u b s t r a t e , t h e OP i n d i c a t e s a h i g h e r e l e c t r o n d e n s i t y (0.698) between the carbonyl carbon and t h e a c e t a t e o x y g e n t h a n the e l e c t r o n d e n s i t y ( 0 . 5 7 9 ) b e t w e e n t h e a l k y l c a r b o n and t h e a c e t a t e o x y g e n due t o p a r t i a l pi-bonding between the a c e t a t e oxygens. However, the ASCh c o r r e s p o n d i n g e l e c t r o n d e n s i t y (0.980) between the c a r b o n y l c a r b o n and the t h i o a c e t a t e s u l f u r i s e v e n l a r g e r due t o e v e n m o r e p a r t i a l p i - b o n d i n g b e t w e e n t h e t h i o a c e t a t e s u l f u r and t h e c a r b o n y l o x y g e n . This enhanced pi-bonding occurs without expanding the atomic b a s i s s e t f o r t h e s u l f u r a t o m t o i n c l u d e e x t r a v a l e n t d_ o r b i t a l s ( 1_2). Since this ester (thioester) linkage i s t h e one w h i c h c o m m o n l y f i s s i o n s i n e s t e r h y d r o l y s i s , i t i s obvious t h a t t h i s r e l a t i v e l y s t r o n g bond must weaken b e f o r e the c h o l i n e ( t h i o c h o l i n e ) m o i t y can depart to conclude the a c y l a t i o n r e a c t i o n . It is observed that the formation of the proposed " t e t r a h e d r a l " intermediate d i s t u r b e s t h i s p a r t i a l pi-bonding such that the e l e c t r o n d e n s i t y o f the e s t e r l i n k a g e f a l l s t o 0.637 (and the t h i o e s t e r l i n k a g e to 0.734), but not to a l o w e r e l e c t r o n d e n s i t y than that of the adjacent a l k y l l i n k a g e . N o t u n t i l a proton i s t r a n s f e r r e d t othe a c e t a t e oxygen (or to the t h i o a c e t a t e s u l f u r ) does the e l e c t r o n d e n s i t y o f the e s t e r l i n k a g e f a l l to 0.485 (and t h a t o f the t h i o e s t e r l i n k a g e to 0.663), both below the e l e c t r o n d e n s i t y of the adjacent a l k y l l i n k a g e . The e l e c t r o n d e n s i t y o f t h e bond f o r m i n g between t h e a t t a c k i n g m e t h a n o l o x y g e n and t h e s u b s t r a t e carbonyl carbon increases s t e a d i l y f o r a l l proposed intermediates, b u t i s i n i t a i l l y l a r g e r f o r t h e ACh s u b s t r a t e ( 0 . 2 2 0 ) than f o r the ASCh s u b s t r a t e (0.074). A l s o , f o r a l l i n t e r m e d i a t e s , the negative a n t i bonding e l e c t r o n d e n s i t i e s between the a t t a c k i n g methanol o x y g e n and t h e t h i o a c e t a t e s u l f u r and c a r b o n y l o x y g e n are l a r g e r than are the corresponding e l e c t r o n d e n s i t i e s

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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310

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Table IV Bond O v e r l a p

Mechanism Step

Population f o r Acylation Intermediates f o r S u b s t r a t e s ACh e n d ASCh

Alkyl C Acetate 0o r Thioacetate S

S u b s t r a t e : ACh

ASCh

Reactants IA IIA 11 I A IV

0.579 0.578 0.588 0.528 0.641

0.670 0.673 0.669 0.665 0.692

Mechanism Step

Methanol 0 Carbonyl C

S u b s t r a t e : ACh Reactants IA IIA 111A IV

ASCh

Carbonyl C Acetate 0o r Thioacetate S

Methanol 0 Acetate 0o r Thioacetate S

ACh

ACh

ASCh

0.698 0.765 0.637 0.485

-

0.980 0.893 0.734 0.663

Methanol 0 Carbonyl 0 ACh

0 0 0 0

.074 .499 .665 .708

-0. -0. -0. -0.

146 104 118 186

_

-0.130 -0.101 -0.134

-0.170 -0.157 -0.155

Carbonyl Carbonyl

C 0

1 .,0 2 0 0..841 0,. 6 5 5 0..664 0,. 9 9 5

0..858 0..981 0.. 6 2 3 0.. 6 3 8 0.. 9 9 5

ASCh

_

0. 2 2 0 0. 5 8 8 0. 6 5 3 0. 7 0 8

ASCh

-0. -0. -0. -0.

161 123 128 186

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

14.

311

Enzymic Hydrolysis of Acetylcholine

coRRiNGTON

f o r the a c e t a t e , h e l p i n g e x p l a i n whythe t o t a l e n e r g i e s f o r the proposed ASCh mechanism s t e p s h i g h e r t h a n f o r t h e c o r r e s p o n d i n g p r o p o s e d ACh steps.

valence were mechanism

Total Overlap Population. While the above study of the i n d i v i d u a l bond o v e r l a p p o p u l a t i o n s i s h e l p f u l i n f o l l o w i n g the changes o c c u r r i n g in the proposed mechanism steps, the t o t a l overlap p o p u l a t i o n , presented in Table V, does not appear to be a u s e f u l v a l u e . T h e t o t a l o v e r l a p p o p u l a t i o n i s the sum over a l l p a i r s o f atoms A and Β o f the o v e r l a p p o p u l a t i o n 0 P defined a b o v e . A l l i n t e r m e d i a t e s and p r o d u c t s have l o w e r t o t a l o v e r l a p than t h e r e a c t a n t s , and t h e a p p a r e n t l y lower energy a c i d c a t a l y z e d pathway does not have the l a r g e s t t o t a l overlap of the three pathways s t u d i e d .

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch014

A B

Total Overlap Energy. However, while t o t a l o v e r l a p p o p u l a t i o n does not appear to be a u s e f u l parameter, the calculated total overlap energy, as presented in Table VI, does. T h e t o t a l o v e r l a p e n e r g y i s t h e sum o v e r a l l p a i r s o f atoms A and Β o f t h e o v e r l a p e n e r g y , OE.g, which i s d e f i n e d s i m i l a r l y to the o v e r l a p p o p u l a t i o n above, but elements of the Η-matrix are used i n p l a c e of elements of the o v e r l a p m a t r i x : 0 E

AB

«

4

^ Σ Σ

H..C. C u

j u

w h e r e i a n d j a r e summed o v e r a l l a t o m i c b a s i s o r b i t a l s and u o v e r a l l m o l e c u l a r o r b i t a l s . In b o t h t h e ACh and A S C h a c y l a t i o n m e c h a n i s m s , t h e t o t a l o v e r l a p energy i s a minimum f o r the a c i d c a t a l y z e d pathway, thus corresponds t o the c a l c u l a t e d t o t a l valence energy. T o t a l o v e r l a p energy a l s o becomes more n e g a t i v e as t h e m e c h a n i s m s t e p s p r o c è d e . A n a l y s i s o f the components of the c a l c u l a t e d t o t a l o v e r l a p energy i n d i c a t e s that in the a c i d c a t a l y z e d pathway the i n d i v i d u a l b o n d e n e r g i e s o f t h e l a r g e ACh o r A S C h i n t e r m e d i a t e s were s t a b i l i z e d by the presence of the i m i d a z o l i u m donated p r o t o n more than the i m i d a z o l i u m was d e s t a b i l i z e d , w h i l e i n t h e b a s e c a t a l y z e d p a t h w a y t h e l a r g e ACh o r A S C h i n t e r m e d i a t e s w e r e d e s t a b i l i z e d by t h e a b s e n c e o f t h e p r o t o n d o n a t e d t o t h e i m i d a z o l by t h e a t t a c k i n g m e t h o x y more t h a n t h e i m i d a z o l w a s stabilized. ( T h e o p p o s i t e was o b s e r v e d t o b e t r u e i n d e a c y l a t i o n w h e n t h e a c y l e n z y m e was m o d e l e d a s the s m a l l e r molecule methyl a c e t a t e (14).)

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Table V

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch014

Total

Overlap

Mechanism Step

Population

I II III IV

ASCh

-0.423 -0.393 -0.544

t o the

reactants) (C) Base Catalyzed

(B) N o n Catalyzed

(A) A c i d Catalyzed

S u b s t r a t e : ACh

(relative

-0.541 -0.591 -0.329

ACh -0.455 -0.377 -0.671 -0.100

ASCh -0.498 -0.402 -0.449 -0.223

ACh

ASCh

-0.909 -0.870

-0.817 -0.802

Table VI Total

Overlap

M e c h a n i sm Step

to reactants)

(B) N o n Catalyzed

(C) Base Catalyzed

ASCh

ACh

ACh

-640 - 4 4 2 -806 - 5 7 9 -816 - 7 2 8

254 121 27 266

(A) A c i d Catalyzed

S u b s t r a t e : ACh I II III IV

Energy (g-kcal/mole, r e l a t i v e

ASCh 236 123 -29 308

959 881

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

ASCh 773 700

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Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch014

C o n c l u s i ons T h i s s t u d y , e m p l o y i n g ARCANA, a s e m i e m p i r i c a l m o l e c u l a r o r b i t a l c a l c u l a t i o n program, to model the a c y l a t i o n step of the enzymic h y d r o l y s i s mechanism f o r ACh and A S C h i n d i c a t e s s i g n i f i c a n t d i f f e r e n c e s i n the M u l l i k e n net a t o m i c c h a r g e s and the o v e r l a p d e n s i t i e s f o r the bonds most i n v o l v e d in the a c y l a t i o n f o r t h e two s u b s t r a t e s a n d t h e p r o p o s e d intermediates. However, t h e s e d i f f e r e n c e s do not seem a s i m p o r t a n t a s the s i m i l a r i t i e s , such a s the l o c a t i o n o f s i m i l a r lowest e n e r g y p i - t y p e empty m o l e c u l a r o r b i t a l s on the p o s i t i v e l y charged carbonyl carbon s u b j e c t i n g i t to n u c l e o p h i l i c a t t a c k , and the s t a b i l i z a t i o n o f s u c h a n a t t a c k b y t h e p r o t o n a t i o n of the n e g a t i v e l y charged carbonyl oxygen. Moreover i n the case o f both s u b s t r a t e s , t h e r e i s s i g n i f i c a n t p a r t i a l pi-bonding in the acetate (or t h i o a c e t a t e ) m o i t y , and p r o t o n a t i o n o f the a c e t a t e o x y g e n (or t h i o a c e t a t e s u l f u r ) i s r e q u i r e d t o d i m i n i s h the e s t e r ( t h i o e s t e r ) l i n k a g e and a l l o w the c h o l i n e ( t h i o c h o l i n e ) t odepart to complete the a c y l a t i o n s t e p . Thus, t h i s study i n d i c a t e s t h a t the a c y l a t i o n step f o r e i t h e r t h e ACh o r t h e A S C h s u b s t r a t e w o u l d p r o c è d e t h r o u g h a low e n e r g y (and thus r a p i d ) a c i d c a t a l y z e d pathway, c o n s i s t e n t with experimental d a t a o n ACh w h i c h suggests that a c y l a t i o n is catalyzed by a f u n c t i o n a l g r o u p o f p K = 5.3 (]J0) a n d w i t h e x p e r i m e n t a l data which show t h a t b o t h ACh and A S C h a r e h y d r o l y z e d a t n e a r l y the same r a t e w i t h t h e s l o w d e a c y l a t i o n s t e p b e i n g the r a t e d e t e r m i n i n g s t e p (5J. Calculation

Note

The t h e o r e t i c a l b a s i s o f t h e m o l e c u l a r o r b i t a l p r o g r a m e m p l o y e d i n t h i s s t u d y , ARCANA, has been developed e l s e w h e r e ( Z j [ , 27) a n d w i l l n o t b e r e p e a t e d h e r e a t l e n g t h . B a s i c a l l y , ARCANA i s a n i n t e r a t i v e e x t e n d e d H u c k l e m e t h o d w h i c h i n c l u d e s n e i g h b o r atom i n t e r a c t i o n s and i t e r a t e s to c h a r g e s e l f - c o n s i s t e n c y . A minimum b a s i s s e t o f i n v a r i e n t b u t o v e r l a p o p t i m i z e d a t o m i c o r b i t a l s (28) a r e e m p l o y e d t o c a l c u l a t e o v e r l a p i n t e g r a l s . The e m p i r i c a l o r b i t a l e n e r g y (29) a n d a n e f f e c t i v e r a d i u s c a l c u l a t e d b y e v a l u a t i n g R. = l / 0 / * \ > f o r a c c u r a t e a b i n i t i o a t o m i c w a v e f u n c t i o n s (30., 3J_) a r e e m p l o y e d t o c a l c u l a t e the Hamiltonian e l e m e n t s . Only the values f o r hydrogen deviate from standard atomic values. R a d i a l moment a n a l y s e s o f a c c u r a t e m o l e c u l a r o r b i t a l s (32) i n d i c a t e d that a contracted, scaled helium-like representation is required f o r hydrogen in a molecule. Table VII summarizes the atomic o r b i t a l parameters employed i n the c a l c u l a t i o n s .

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

314

COMPUTER-ASSISTED DRUG DESIGN

Table Orbital Element

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch014

Orbital

H

Is

C

2s 2p 2s 2p 2s 2p

Ν 0 a

Parameters n

VII

Employed

ST0

Z

Orbital Energy (eV)

ST0

l

a

2

b

1.57 0.88°

b

1 .88 1.06

1 .45

a

2

l

b

b

ϋ l

2

b

b

2.19K 1.22

R e f . 32_, b R e f . 2 8 , c R e f .

b

- 9.0

a

e

- 1 9 . 5. - 9.9

b

l

i n ARCANA C a l c u l a t i o n s

b

-25.5? -12. 5

C

C

e

-32.0 . -15.3 e

R, = l / < l / r > (a.u.) 1

0.65

a

1.12* 1 .28

d

0.94* 1 .04

d

0.80*J 0.90°

29., d R e f . 3 1

A f t e r i t e r a t i n g t o charge s e l f - c o n s i s t e n c y , a total valence energy i s c a l c u l a t e d . This includes appropriate factors f o r valence electron repulsion (but excludes the core electrons) andincludes nuclear repulsion (but excludes the corresponding core nuclear charges). A recent comparison (33) o f q u a n t i t i e s c a l c u l a t e d from m o l e c u l a r e l e c t r o n i c wave f u n c t i o n s f o r p y r r o l e a n d p y r a z o l e i n d i c a t e d t h a t ARCANA v a l u e s c o m p a r e d more f a v o r a b l y with l a r g e - s c a l e ab i n i t i o values than those c a l c u l a t e d by other non-rigorous methods i nthe case o f orbital energies o foccupied molecular o r b i t a l s , gross atomic populations o f heteroatoms, andtotal overlap populations including negative overlap populations between nonbonded atoms. Acknowledgements The a u t h o r wishes t o thank t h e f o l l o w i n g s t u d e n t r e s e a r c h a s s i s t a n t s f o r t h e i r c o n t r i b u t i o n s t o t h i s work: W a r r e n W e l t e r s , Ramona C a l v e y , D e b r a Simmons, C h e r y l Mackie, Mary Dean, a n dL a r r y Givens. T h i s s t u d y was s u p p o r t e d b y Grant RR-08008 from t h e General Support Branch, D i v i s i o n o f Research Resources, National I n s t i ­ tutes o f Health. Literature Cited

1. Scott, K. A. and Moutner, H. G . , Biochem. Pharmacol., 13, 907 (1964)

2. Mautner, H. G., Bartels, E. and Webb, G. D., Biochem. Pharmacol., 15, 187 (1966)

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch014

14.CORRINGTONEnzymic Hydrolysis of Acetylcholine

315

3. Mautner, H. G., J. Gen. Physiol., 54, No. 1, Pt. 2, 2715 (1969) 4. Mautner, H. G., Dexter, D. D . , and Low, B. W., Nature (London), New Biology, 238, 87 (1972) 5. Scott, K. A. and Mautner, H. G . , Biochem. Pharmacol., 13, 907 (1964) 6. Froede, H. C. and Wilson, J . B . , Enzymes, 3rd E d . , 5, 87 (1971) 7. Wilson, I. B. and Bergmann, F., J. Biol. Chem., 186, 683 (1950) 8. Krupka, R. M . , Biochem., 5, 1983 (1966) 9. Krupka, R. M . , Biochem., 5, 1988 (1966) 10. Krupka, R. M . , Biochem., 6, 1183 (1967) 11. Pullman, B. and Courriere, P . , Mol. Pharmacol., 8, 371 (1972) 12. Aldrich, H. S., Int. J. Quantum Chem., Quantum Biol. Symp., 2, 271 (1975) 13. Farkas, M . , Kruglyak, Υ. Α . , Nature (London), 223, 523 (1969) 14. Corrington, J . Η. (submitted) 15. Genson, D. W. and Christoffersen, R. F., J. Amer. Chem. Soc., 95, 362 (1973) 16. Camepa, F. G . , Pauling, P . , and Sorum, H . , Nature (London), 210, 907 (1966) 17. Herdklotz, J . K. and Sass, R. L., Biochem. Biophys. Res. Commun., 40, 583 (1970) 18. Clothia, C. and Pauling, P. J., Nature (London), 223, 919 (1969) 19. Smissman, Ε. E. and Chappell, G. S., J . Med. Chem., 12, 432 (1969) 20. Smissman, E. E., Helson, W. L., LaPidus, J . B. and Day, J. L., J. Med. Chem., 9, 458 (1966) 21. Stephen, W. F., Jr., Smissman, E. E., Schowen, Κ. B . , and Self, G. W., J. Med. Chem., 15, 241 (1972) 22. Schowen, Κ. B . , Smissman, Ε. Ε . , and Stephen, W. F . , Jr., J. Med. Chem., 18, 292 (1975) 23. Shefter, E., Mautner, H. G., and Smissman, Ε. E., Acta Crystallogr. Sect. A, 25, S201 (1969) 24. Rerat, C., Bull. Soc. Franc. Min. Crist., 85, 153 (1962) 25. Mulliken, R. S., J . Chem. Phys., 23, 1833, 1841 (1955) 26. Corrington, J . Η., Aldrich, H. S., McCurdy, C. W., and Cusachs, L. C., Int. J. of Quantum Chem., 5, 307 (1971) 27. Cusachs, L. D. and Miller, D. J., Advan. Chem. Ser. 110, 1 (1972) 28. Cusachs, L. C. and Corrington, J . H . , "Atomic Orbitals for Semiempirical Molecular Orbital Calculations," in Sigma Molecular Orbital Theory, Sinanoglu, O.,

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

316

29. 30. 31. 32.

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33.

COMPUTER-ASSISTED

DRUG

DESIGN

and Wiberg, Κ. B., e d s . , (Yale University Press, New Haven, Conn., 1970), p. 256 Cusachs, L . C. and Reynolds, J. W., J. Chem. Phys., 43, S160 (1965) Clementi, E., J. Chem., Phys., 41, 295, 303 (1964); J. Chem. Phys., 38, 996, 1001 (1965), IBM J. of Res. and Dev., 9, 2 (1965) Froese, C., J. Chem. Phys., 45, 1417 (1966) and supplement and private communication Cusachs, L . C. and A l d r i c h , H. S . , Int. J . Quantum Chem., 6S, 221 (1972) Kaufman, J. J., Preston, H. J. T., Kerman, E., and Cusachs, L. C., Int. J. of Quantum Chem., 7S, 249 (1973)

Received June 8, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

15 A New Approach to Bioactive Synthesis PHILIP S. MAGEE

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch015

Chevron Chemical Co., 940 Hensley Street, Richmond, CA 94804

The application of QSAR to bioactive synthesis has always suffered f r o m an unfortunate paradox. In order to develop a useful equation, it is necessary to first complete a substantial fraction of the synthesis. Only then can the derived equation assist in extending or optimizing the bioactive series. No help is available for the earliest or intermediate stages of synthesis which have already been passed. Nor is it certain that a useful equation can be gained f r o m the first 10-20 members of a series. Poor selection of structural changes, variable biodata, differential metabolism of some members and the p r e sence of unknown factors can a l l lead to poor correlations of little practical use. These problems are common to anyone who has attempted QSAR on novel bioactive series. There is another problem that is equally vexing and this relates to drug or pesticide modification. In most cases, the complete structural series and biodata were developed in another laboratory and are unavailable. The only available knowledge may be the structures of the c o m m e r c i a l and patented bioactives. No equation is forthcoming unless the entire study is repeated in your own laboratories, a project unlikely to gain approval. How then can one apply computer assisted methods based on QSAR to aid synthesis at any stage in either type of problem? Inventive use of the transport, enzyme association and reaction model in conjunction with a large operational table of physically measured parameters provides a partial solution.

0-8412-0521-3/79/47-112-319$05.50/0 © 1979 American Chemical Society

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COMPUTER-ASSISTED DRUG DESIGN

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The N e c e s s a r y Models T h e a p p r o a c h depends on f a m i l i a r s t r u c t u r a l and b i o e n e r g e t i c m o d e l s . In the s t r u c t u r a l m o d e l , a b i o a c t i v e s e r i e s i s d e s c r i b e d as a p a r e n t s y s t e m p l u s s u b s t i t u e n t s . We w i l l d e a l o n l y w i t h s u b s t i t u e n t s and t h e i r effects on s t r u c t u r e r a t h e r than w i t h w h o l e m o l e c u l e s . A w h o l e m o l e c u l e a p p r o a c h i s not i m p o s s i b l e but p o s e s m o r e p r o b l e m s i n its d e s i g n . F i g u r e 1 shows a s i m p l i f i e d v e r s i o n of the b i o e n e r g e t i c m o d e l l e a d i n g to the g e n e r a l H a n s c h equation. Transport from p o i n t of a p p l i c a t i o n to the r e g i o n c o n t a i n i n g the a c t i v e s i t e , r e p r e s e n t e d h e r e as an enzyme, i s shown. F o r p a s s i v e t r a n s ­ p o r t , the d e p e n d a n c y i s s o m e f u n c t i o n of l o g Ρ o r the d e r i v e d p a r a m e t e r , π. S u b s t r a t e b i n d i n g , h o w e v e r , m a y depend on π o r M R a c c o r d i n g to the n a t u r e of the a s s o c i a t i o n s i t e . I n h i b i ­ t i o n is then c o n s i d e r e d to be an o r g a n i c r e a c t i o n l i k e l y to c o r ­ r e l a t e w i t h e l e c t r o n i c and s t e r i c p a r a m e t e r s . F i n a l l y , the s e q u e n c e of events that f o l l o w i n h i b i t i o n l e a d s to a m e a s u r e d bio r e s p o n s e that c a n be c a s t into f r e e - e n e r g y f o r m by the e x p r e s s i o n L o g 1 / Ε Ό 5 0 · F o r a r e l a t e d s e r i e s of compounds, we then a c c e p t the l i n e a r c o m b i n a t i o n o f f r e e e n e r g y f a c t o r s b a s e d on s u b s t i t u e n t constants as b e i n g f r e q u e n t l y c a p a b l e o f c o r r e l a t i n g the biodata.

Appln.

/ n

-V

-

phases

/

V

y

©==; (R

/

/ Transport Log Ρ , π

Binding 7Γ, MR

log 1 / E D

5 0

= a7T-

Figure 1.

b7T + cG 2

Inhibition a's,u,E s

+ dU + e

QSAR model

T h e i m p o r t a n t p o i n t of this m o d e l is that we r e s t r i c t o u r ­ s e l v e s to s i m p l e t r a n s p o r t , b i n d i n g and r e a c t i o n p a r a m e t e r s .

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

15.

MAGEE

321

Bioactive Synthesis

M a s t e r Data T h e k e y to c o m p u t e r a s s i s t e d s y n t h e s i s b a s e d on t h e s e m o d e l s l i e s i n the s i z e a n d f o r m a t o f the data b a s e . In i t s c u r r e n t v e r s i o n , the M a s t e r D a t a p a r a m e t e r t a b l e l i s t s 390 s u b s t i t u e n t s i n 780 l i n e s . A s shown i n F i g u r e 2, e a c h s u b s t i ­ tuent i s e n t e r e d on two l i n e s . T h e o d d l i n e s c o n t a i n the m e t a p a r a m e t e r s ; the even l i n e s c o n t a i n the p a r a a n d a l i p h a t i c v a l u e s . F o l l o w i n g the c a s e n u m b e r a n d a s i m p l i f i e d s u b s t i t u e n t name, the h e a d i n g s a r e : m o l e c u l a r w e i g h t of f r a g m e n t , m o l a r r e f r a c t i o n , p i , p i s q u a r e d , Hammett's s i g m a , B r o w n s s i g m a p l u s , C h a r t o n ' s s i g m a l o c a l i z e d and C h a r t o n s u p s i l o n v a l u e s . 1

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch015

!

CASE

NAME

MWF

MR

El

PIQ

SIG

SIGP

SIG1

17 18

CN CN

26.0 26.0

6.33 6.33

-0.57 -0.57

0.32 0.32

0.56 0.66

0.56 0.66

0.60

701 702

SOME SOME

63.1 63.1

13.70 13.70

-1.58 -1.58

2.50 2.50

0.52 0.49

0.39

Figure 2.

Master data

O r i g i n a l l y d e s i g n e d as a data b a s e f o r m u l t i p l e r e g r e s ­ s i o n , the m a i n t a b l e has s e v e r a l s u b - t a b l e r o u t i n e s f o r c o m ­ bining selected lines with kinetic, e q u i l i b r i u m o r biodata. One of the r o u t i n e s c o n v e r t s b i o d a t a i n ppm, a c o m m o n i n d u s t r y f o r m , to the m o l a r e q u i v a l e n t , l o g MW/ED50. T h i s i s gene­ r a t e d b y i n t r o d u c i n g the p a r e n t MW into a p r o g r a m that u s e s MWF f r o m M a s t e r Data. T h e m o s t i m p o r t a n t f e a t u r e of M a s t e r D a t a i s the s i m p l e data b a s e f o r m a t . T h i s a l l o w s m a n i p u l a t i o n o f the data by c o m p u t e r p r o g r a m s d e s i g n e d to a s s i s t s y n t h e s i s . T o f a c i l i t a t e use of these p r o g r a m s , M W F and e a c h o f the p a r a m e t e r s a r e a s s i g n e d a n u m e r i c a l c o d e (1-8) as c o l u m n i d e n t i f i e r s . In the f o l l o w i n g s e c t i o n s , the M a s t e r D a t a p r o g r a m s a r e described with relevant examples. RANGE Program

- Isolipophilic

Groups

M a n y drug and p e s t i c i d e s e r i e s a r e either t r a n s p o r t o r b i n d i n g dependent and e x h i b i t o p t i m u m b e h a v i o r i n l o g Ρ o r i n s u b s t i t u e n t π v a l u e s . T h i s i s o f t e n a p p a r e n t f r o m the s t r u c ­ t u r e s of c o m m e r c i a l m e m b e r s o f a c l a s s . W i t h i n a f a c t o r o f two o f the o p t i m u m ( l o g 1/C-O. 3), the w i d t h o f m o s t p a r a b o l i c o r b i l i n e a r p l o t s i s 1. 5-3. 0 l o g Ρ u n i t s (JO. T h u s , i f a c l a s s i s l o g Ρ o r Σ π dependant, its b e s t m e m b e r s s h o u l d c l u s t e r about

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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322

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch015

the o p t i m u m w i t h the m a j o r i t y f a l l i n g i n the r a n g e , l o g Ρ (avg) +_ 1. 0. F i g u r e s 3 and 4 show f o u r d r u g s e r i e s that f i t this criterion.

Diuretic

Local Anesthetic

Figure S.

Some drug classes

PROBABLE TRANSPORT OR BINDING DEPENDANCE Class

Avg. Σπ

Range (±1.0)

No. in Range

η

Barbiturates

3.23

2.23-4.23

30

34

Antipsychotics

1.43

0.43-2.43

19

22

Diuretics

2.58

1.58-3.58

14

16

Local Anesthetics

2.32

1.32-3.32

15

18

Figure 4.

Probable transport or binding dépendance

C o n c e n t r a t i n g on one o f t h e s e c l a s s e s , we note i n F i g u r e 5 that 27 o f 34 c o m m e r c i a l b a r b i t u r a t e s h a v e e t h y l o r a l l y l as one of the g e m - d i a l k y l groups(2). in designing a prog r a m to r e p l a c e e t h y l o r a l l y l w i t h n o v e l g r o u p s , the m o s t c o m m o n c a u s e o f low a c t i v i t y c o u l d w e l l be s e r i o u s d e p a r t u r e

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

15.

MAGEE

Bioactive Synthesis

323

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch015

f r o m optimum log P. What is really needed then is a design program for novel isolipophilic groups. Such groups may still fail to excell but not because they possess inadequate π values.

Mephobarbital

C-Alkyl

No. of Cases

C H 2

15

5

CH =CHCH 2

2

(CH ) CH3

Talbutal

2

Figure 5.

Allobarbital

η 34

1.02

12

34

1.10

5

34

1.40

Various barbiturates

In a simplistic approach, Master Data can be rapidly searched by a PL/1 program called R A N G E for groups having π values close to ethyl and allyl. R A N G E is activated by selecting the parameter code for π (=2) and specifying the lower and upper limits of the search. The program segregates the desired data, ranks it in ascending order and prints out within seconds. Response on a C R T terminal is immediate. This is useful, but a more inventive approach uses group fragments called R A N G E modifiers. Shown in Figure 6 are a few of the groups used to modify any selected range of π values by combining these groups with those on the program print-out. In this procedure, we are taking advantage of an approximation, the near additivity of π values. Since these groups contribute to the total π value,

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

324

their values must be subtracted f r o m the range being searched. RANGE MODIFIERS

-s-

-CN

-0-

-OCH3

-CH=CH-

-SCN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch015

/C=0

-co> C H

3

-N(CH ) 3

-(CH ) -

-SCH3

-so2-

-S0 CH

2

-CI, Br

Figure 6.

n

2

2

3

Range modifiers

As shown in Figure 7, if three - C H 2 - groups are added to substituents printed out by the R A N G E program, then clearly this contribution must be subtracted to stay in the desired range. MODIFIER CORRECTION MODIFIER

ΤΓ

CORRECTION

-(CH ) -

1.55

-1.55

-CH=CH-

0.82

-0.82

-0.02

+0.02

>=0

-1.06

+1.06

-SO 9-

-2.14

+2.14

2

-0CH

3

3

Figure 7.

Modifier correction

In actual practice, the R A N G E problem of generating groups isolipophilic with ethyl-allyl would be handled as follows. A s both groups are close in π value, a single nominal range of 1. 02-1. 10 can be used. This range is a r b i t r a r i l y extended to accommodate e r r o r s in π and to avoid missing adjacent groups of interest. A n extension of 0. 3 was selected for this problem, a value which includes two other s m a l l groups used in barbiturates, vinyl (π = 0. 82) and isopropyl (π = 1.40). The extended range (0. 72-1.40) is now broadened to cover a l l modifiers in a single run (search range = -0. 83 to 3. 54. A s the print-out is ranked in π, it is simple to mark and label the top

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch015

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Bioactive Synthesis

325

and bottom of each modifier. Within these individual ranges, one looks for interesting groups to combine with the modifiers. The near additivity of π values is an approximation, but the width of most log Ρ curves is such that few outliers w i l l be generatedQ). It should be remembered that no attempt is being made to duplicate exact numbers but simply to fall within o r near a selected range. Because of this scope and "margin for error", the combination process of modifier + print-out groups can be highly inventive, with cyclizations and isomerizations freely allowed. Figure 8 shows a few of the many groups generated as ethyl/allyl replacements. Note that part of the inventive process includes casting the isolipophilic group into a suitable intermediate for the desired reaction, alkylation of malonic ester in this case. Master Data and the R A N G E program is merely an assistant or co-inventor at best. Human inventive skills are still required to complete the procedure. The potential for generating novel isolipophilic groups is nearly unlimited even though Master Data is presently far f r o m com­ plete in π values.

Isolipophilic Reactant

-SCH

3

-CH CH OCH

3

-CH CH OCH

3

2

2

2

-N(CH ) 3

2

-CH CH=CH

2

2

C1

CH OCH CaCCH C1 3

2

2

(CH ) NCH=CHCH C1

2

3

2

2

Ο

Ο

II

-CH C(CH )

-c-

2

3

II

3

(CH ) C-CCH Br 3

Example: C H O C H C s C C H C 1 + 0 C ( C O O C H ) 3

2

2

2

Η

Ν. CH OCH CsCCH 3

2

2

5

3

2

2

Ο Σπ = 2.93

Figure 8. Groups isolipophilic with C H —C H 2

5

S

5

Figures 9 and 10 describe a similar pesticide example based on the Stauffer Chemical series of thiolcarbamate herbicides. The implied optimum in transport or binding is

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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c l e a r f r o m i n s p e c t i o n of F i g u r e 9, t h e s e f o u r b e i n g the s t r o n g e s t of the s e r i e s . T h e p r o b l e m c h o s e n w a s r e p l a c e m e n t of the R S - a l k y l g r o u p w i t h g r o u p s i s o l i p o p h i l i c w i t h e t h y l / p r o p y l . A s s e e n i n F i g u r e 10, the r a n g e s e a r c h e d i s n e a r l y the s a m e as that f o r e t h y l / a l l y l . T h i s i s c o i n c i d e n t a l and i m p l i e s no l i m i t a t i o n s o n the p r o c e d u r e . A n y g r o u p f r o m m o s t l i p o p h i l i c to m o s t h y d r o p h i l i c c a n be p r o c e s s e d . F i g u r e 10 a l s o c o n t a i n s an i n t e r e s t i n g e x a m p l e of the i n v e n t i v e p r o c e s s . In the t h i r d e x a m p l e , the v a l e r o l a c t o n e g e n e r a t e d f r o m the c a r b o x y l m o d i f i e r a n d the b u t y l g r o u p i s d i f f i c u l t to p r e p a r e but the i s o m e r i c b r o m o b u t y r o l a c t o n e i s a v a i l a b l e f r o m A l d r i c h Chemical.

^z»CH CH CH 2

EPTAM

2

3

CH CH SCI\k 3

2

CHOCHQCH

?

ORDRAM

^CHoCHoCHo CH CH CH 2

0 VERNAM

2

2

•CH0CH0CH0

CH CH CH S(!l\lc = i x

^

GRISEOFULVIN

® "

s

\ — ™

X

INHIBITION BY MICHAEL ADDITION

Figure 11.

Fungicides inhibiting dehydrogenases

F r o m a p a t t e r n r e c o g n i t i o n p o i n t o f view, o v e r 5 0 % o f c o m m e r c i a l f u n g i c i d e s a r e , i n fact, S H i n h i b i t o r s (4). These t h r e e s y s t e m s r e p r e s e n t a b r o a d g e n e r a l c l a s s and h a v e i n c o m m o n a n i n h i b i t i o n step r e l a t e d to t h e M i c h a e l a d d i t i o n . T h e R A N G E p r o g r a m c o u l d b e u s e d to e x a m i n e e a c h fungicide i n d i v i d u a l l y f o r the p u r p o s e of i m p r o v i n g each c l a s s . B u t a m u c h m o r e i n t e r e s t i n g a p p r o a c h i s to t r e a t the M i c h a e l a d d i t i o n i t s e l f . T h i s c a n b e done b y c o n s i d e r i n g the e l e c t r o n i c r a n g e o f t h o s e g r o u p s k n o w n to a c t i v a t e the d o u b l e bond f o r n u c l e o p h i l i c a d d i t i o n . F i v e o f the n i n e g r o u p s s e l e c t e d f o r t h i s s t u d y a r e shown i n F i g u r e 12 a n d t h e s e i n c l u d e the two g r o u p s at e a c h end o f t h e r a n g e (-NO2 a n d - C O N H 2 ) . S i g m a p a r a (σρ) w a s s e l e c t e d to r e p r e s e n t t h e e l e c t r o n i c r a n g e o f t h e s e g r o u p s b e c a u s e o f its h i g h r e s o n a n c e component. A m u c h b e t t e r c h o i c e w o u l d b e one o f C h a r t o n s s i g m a d e l o c a l i z e d p a r a m e t e r s !

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

15.

MAGEE

Bioactive Synthesis

-N0

329

0.78

2

-S0 CH 2

0.72

3

-CN

0.66 0.45

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch015

-COOCH3

-CONH

0.36

2

RANGE

0.36-0.78

SEARCH

0.3 - 0.9

Figure 12.

Michael addition activators (—CH=CH—X)

(σ£> or < : = /

X

(ΟΗ ) 0(:ΗΟΕΪ 2

°9

4

CH CO H 3

2

P h

Ph Q

νΡ

(CH^C^OH

2 C r Q

^

· o-^ph

5

Ph

X^'\=/ V

O'

( C H 2 ) 3 C 0 2 H

Li/NH

3

: I

OCPh

Ph

oh

: OH

Figure 2.

Syntfgt^^Jf^^

Society Library 1155 fetb St. N. w. In Computer-Assisted Drug Olson, E., el al.; Washington, D.Design; C. 20036 ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

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preclude r e a c t i o n A. A t y p i c a l A and Β p a i r are h y d r o l y s i s of an e s t e r and hydrogénation of an i s o l a t e d carbon-carbon double bond. In such a case, as we p r o g r e s s backward from the molecule with s u b s t r u c t u r e s X and Y* t o the molecule with s u b s t r u c t u r e s X and Y we can reach the l a t t e r along two paths, i . e . A then Β o r Β then A. For b r e v i t y we can describe the s i t u a t i o n as ΧΥ->Χ'Υ+Χ'Υ' and ΧΥ+ΧΥ'-^Χ'Y . Before we c a l l i n r e a c t i o n Β on product XY t o generate r e a c t a n t XY we should f i r s t i n q u i r e whether the pathway from XY t o X'Y' through X'Y has p r e v i o u s l y been considered by the program. Since we do not r e t a i n any molecular s t r u c t u r e not i n the d i r e c t l i n e o f ascent to the g o a l molecule from the c u r r e n t molecule XY', t h i s means t h a t we cannot ask the simple question "Has X'Y been generated p r e v i o u s l y ? " Instead we have to get a t t h i s i n f o r m a t i o n i n d i r e c t l y . We can ask whether the r e a c t i o n Β has been performed t o produce the molecule X'Y . For each molecule whose s t r u c t u r e i s s t i l l s t o r e d i n the memory, a record i s kept of a l l the r e a c t i o n s simulated which g i v e r i s e to the molecule as a product. For each of these r e a c t i o n s the p a r t i c u l a r i n s t a n c e i n the molecule of the s u b s t r u c t u r e produced i s a l s o noted. Hence we can get a d e f i n i t e answer as t o whether Β has p r e v i o u s l y been used as a r e a c t i o n i n which X'Y i s the product. I f i t was not, we have no d u p l i c a t i o n problem here. I f Β was simulated to produce X'Y* then we have t o ask whether A i s i n t e r f e r e d with by Y. I f so, then there was no sequence AB. I f not, then there must have been a sequence AB; consequently we should avoid r e a c t i o n Β p r e c e d i n g A. In r e a l l i f e , i n the program, t h i s means t h a t we have t o ask these questions before u s i n g any r e a c t i o n except those t h a t produce the g o a l molecule directly. 1

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch016

1

1

1

1

There e x i s t of course, such sequences of "commuting" r e a c t i o n s as ABC, BCA and CAB. We have not programmed the e l i m i n a t i o n o f these t r i p l e occurrences y e t but are p l a n n i n g t o do so. 2.

L i m i t a t i o n on the number of steps. At i n p u t time the user s p e c i f i e s the maximum number of steps f o r an acceptable s y n t h e s i s . T h i s c u t s o f f the bottom of the t r e e (problem " t r e e s " grow downward). T h i s d e v i c e i s sine qua non but by i t s e l f i t i s s t i l l q u i t e a weak c o n s t r a i n t . 3. Minimum requirement f o r the o v e r a l l y i e l d . T h i s i s a l s o s p e c i f i e d a t input time by the user. 4. Minimum requirement f o r the y i e l d of the l a s t three steps. As everyone knows who has done syntheses e x p e r i m e n t a l l y , the amount o f m a t e r i a l that has t o be c a r r i e d through the v a r i o u s steps i s most important. I f there are low y i e l d i n g steps they should be near the beginning of the s y n t h e s i s r a t h e r than near the end. T h i s f a c t o r i s not n e c e s s a r i l y r e f l e c t e d i n the o v e r a l l y i e l d . Consequently, i n the program i t s e l f there i s the

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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requirement that the overall yield of the last three steps must be at least 35%. This means that the middle of the tree i s pruned rather drastically. The user does not specify the 35% parameter. Obviously i t could be altered i n minutes but most users have no objection to this value so we do not burden the user with this decision. 5. Limitation on the use of f a c i l i t a t i n g reactions. Building reactions can be used wherever appropriate but f a c i l i t a t i n g reactions can only be used i f they were called for specifically. The " c a l l " can come from the failure of a building reaction to proceed on account of interference with the reaction for some functional group i n the molecule. In such a case the group must be protected and, since we are proceeding backwards from the goal molecule, the reaction to remove protection from this functional group i s called i n . If the number of different kinds of groups to be protected exceeds the limit of the successive number of the f a c i l i t a t i n g reactions imposed by the user then none of the protections are effected. Sometimes f a c i l i t a t i n g reactions are called i n by reaction product derivation routines. An example i s the change of functionality required to obtain a six membered ring at hand from one which i s the product of a plausible Diels-Adler reaction. This single heuristic has resulted i n a drastic reduction of the number of reactions simulated by the program in investigating a problem. For example, the Depo-provera synthesis was found after simulating only 280 reactions and the t o t a l number of reactions simulated was only 1385. This was obtained using input requirements of 8 for the upper l i m i t on the number of steps, 3 for the upper limit on the number of consecutive f a c i l i t a t i n g reactions and 5% for the lower bound on the overall yield of the synthesis. Before introducing this heuristic we had been used to generating 20,000 to 200,000 molecular structures in a run. The exact number of reactants generated by the program in investigating a synthetic problem of any complexity w i l l vary with almost any slight change in the program. It i s increased by adding reactions to the program and of course i t i s decreased by refining the scope and limitations of any reaction i n the program. 6. Requirement for compatibility with a starting sturcture. This i s the requirement that the skeleton of substructures which are present i n both the starting material and the goal molecule may not be altered. This pruning device i s optional. Ordinarily i t i s not used when the problem thinks backward from the goal molecule without any particular direction i n mind. Any substance which satisfies the input restrictions on the number of chiral centers, functional groups and rings i s considered to

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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COMPUTER-ASSISTED DRUG DESIGN

be a v a i l a b l e and the program d e c l a r e s a s y n t h e s i s t o be found i f i t reaches an a v a i l a b l e substance i n i t s backward search. For complex s t r u c t u r e s , t h i s i s an extremely important tree pruning method. When we are t h i n k i n g i n the forward d i r e c t i o n about a s y n t h e s i s the requirement of c o m p a t a b i l i t y with a s t a r t i n g s t r u c t u r e i s a u t o m a t i c a l l y s a t i s f i e d . As soon as we s t a r t to t h i n k backward from the goal molecule, the question of the d e s c r i p t i o n of the s t a r t i n g m a t e r i a l a r i s e s . At f i r s t thought i t seems f a r more elegant to ignore t h i s question; we simply work backward and as soon as we reach an acceptably simple molecule o r an a v a i l a b l e molecule, we have completed a s y n t h e s i s p l a n . However, t h i s o f t e n r e s u l t s i n u n i n t e l l i g e n t behavior. To see t h i s , l e t us consider a s t r i n g A-B-C-D, where A,B,C and D are s t r u c t u r a l fragments. Suppose t h a t on the l i s t of a v a i l a b l e substances i s A-B and C-D. Now the program "knows" t h a t A-B and C-D are a v a i l a b l e but i t accesses t h i s knowledge o n l y under a s i n g l e f i x e d circumstance, i . e . a new r e a c t a n t has been generated i n the course of s i m u l a t i n g a r e a c t i o n and the program compares the s t r u c t u r e of t h i s r e a c t a n t with those on i t s l i s t of a v a i l a b l e substances. But the program does not keep i t s a t t e n t i o n on the a v a i l a b i l i t y of A-B and C-D when i t i s s e l e c t i n g a r e a c t i o n t o simulate. For example, i t may generate A-B-C from A-B-C-D. Then i t may generate A-B from A-B-C and thus a two step process. But i n f a c t the one step process of j o i n i n g A-B to C-D may e x i s t and the program w i l l not immediately f i n d i t . I f the planner i n the program decides t h a t the s y n t h e s i s must proceed from A-B and C-D then the only problem remaining i s t o see i f the bond j o i n i n g Β t o C i n the goal molecule can be made. I f so, then the one step s y n t h e s i s i s immediately uncovered. We encountered analogous advantages of d e c i d i n g on a s t a r t i n g skeleton i n more complex circumstances. I f we are seeking a t o t a l s y n t h e s i s of a s t e r o i d , f o r example, and we have the B/C r i n g system already formed i n the s t a r t i n g m a t e r i a l , then the problems to be solved are the a d d i t i o n of the A and D r i n g s , not the formation of the Β and C r i n g s . However, when t h i n k i n g backward from the goal molecule, without a d e f i n i t e s t a r t i n g s k e l e t o n i n view, a program can e a s i l y l o s e i t s way, now adding p i e c e s of the A r i n g , then adding p i e c e s of the C r i n g , e t c . There tends t o emerge, a f t e r much searching and many steps down the s y n t h e t i c t r e e , a h i g h l y branched s t r u c t u r e that has many c h i r a l centers and i s as d i f f i c u l t to make as a s t e r o i d . Such was the u s u a l experience on asking the program to synthesize a s t e r o i d . With a s u i t a b l e upper l i m i t on the number o f c h i r a l centers r e q u i r e d f o r a s t a r t i n g m a t e r i a l t h a t i s not on the a v a i l a b l e substance l i s t , the program does not a c t u a l l y propose such a s y n t h e s i s , but i n v e s t i g a t i o n showed t h a t these were the l i n e s along which much of the u s u a l l y f r u i t l e s s search was proceeding. To avoid t h i s there was i n c o r p o r a t e d i n t o the program a planning r o u t i n e which a t the outset of the problem s o l v i n g process decides on a s t a r t i n g skeleton. When the planner

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch016

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i s given c o n t r o l , no r e a c t i o n simulated may b u i l d t h i s s k e l e t o n . The p l a n n i n g r o u t i n e uses the s t a r t i n g s k e l e t o n f o r a g i v e n number of simulated r e a c t i o n s , e.g. 32,000 and then chooses another s t a r t i n g skeleton and so on u n t i l an acceptable s y n t h e s i s i s found o r the time allowed f o r the job i s exhausted. The f i r s t choice f o r the s t a r t i n g s k e l e t o n i s t h a t input by the user. The second choice i s t h a t imposed by a r e q u i r e d s t a r t i n g substance. The t h i r d choice c o n s i s t s o f a p a r t i c u l a r r i n g o f the s t r u c t u r e of the g o a l molecule. Which r i n g should the s t a r t i n g m a t e r i a l contain? The a l g o r i t h m i c answer t o t h i s question u l t i m a t e l y must be provided by many experienced s y n t h e t i c organic chemists. Corey(12) p r o v i d e d a f i r s t answer t o t h i s question f o r the case of b r i d g e d r i n g systems. However, subsequently Johnson's very e f f i c i e n t s y n t h e s i s o f l o n g i f o l e n e ( 1 3 ) which made two r i n g s a t a time, v i o l a t e d Corey's p r e l i m i n a r y r u l e s by making a bond t h a t was not " s t r a t e g i c " a t the c r u c i a l s t e p . E v i d e n t l y the theory needs refinement. P a r t i c u l a r l y , there i s no theory about an unbridged system. F o r example, we cannot say whether the most convergent s y n t h e s i s o f a s t e r o i d s t a r t s with the A and Β r i n g s or the Β and C r i n g s , e t c . Presumably the answer depends on what f u n c t i o n a l i t y i s around the skeleton, which methyl groups and C-17 s u b s t i t u e n t s are present, e t c . I t may even depend on what r e a c t i o n s have been invented, e.g. m i c r o b i a l o x i d a t i o n a t C - l l : most p r a c t i c i n g chemists are h i g h l y l i k e l y t o conclude t h a t general p r i n c i p l e s are not d i s c o v e r a b l e because they do not e x i s t . The p l a n n i n g r o u t i n e d e s c r i b e d here takes f o r the time being an ad hoc approach o f t r y i n g everything, i . e . each r i n g i s t r i e d s e p a r a t e l y as a s t a r t i n g skeleton and then a l l p o s s i b l e p a i r s o f r i n g s are used. As the general p r i n c i p l e s emerge they w i l l be i n c l u d e d , t o replace the ad hoc approach. 7. Requirement f o r success i v e l y b e t t e r syntheses. A f t e r f i n d i n g an η step s y n t h e s i s the program changes i t s requirements so t h a t any f u r t h e r s o l u t i o n s can be no longer than n-1 steps and must have a higher o v e r a l l y i e l d than t h a t already achieved i n the η step s y n t h e s i s . Acknowledgement: The author g r a t e f u l l y acknowledges f i n a n c i a l support f o r t h i s work from the N a t i o n a l Science and Engineering C o u n c i l o f Canada.

ABSTRACT A report is given about a program that proposes many-step syntheses for a given organic compound, without interacting with the user after the i n i t i a l description of the problem. The problem description includes the structure of the desired goal molecule, complete with chirality, the maximum number of steps for an acceptable synthesis and the minimum overall yield required. Optionally, the problem description may also include

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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the specification of acceptable starting materials. These may be specifically stated, or generally indicated, i.e. with a given skeleton. The maximum number of rings, functional groups and chiral centers for an acceptably simple starting material may also be given. An eight step synthesis of the contraceptive Depo-Provera proposed by the program, which starts from progesterone, is presented. A short prostaglandin synthesis, similar to one reported in the literature, was also proposed by the program. Various ways of managing the combinatorial explosion problem were described. Basically we want to maximize the number of building reactions and minimize the number of facilitating reactions. The facilitating reactions should not be suggested unless they actually facilitate a specific building reaction. There must also be an upper limit on the number of sequential facilitating reactions that may be performed without doing any building reactions.

Literature Cited 1. Finch, A . F . , to be published in J . Chem. Inf. & Comp. Sci., (1979) 2. Fugmann, R., "The IDC System" in "Chemical Information Systems", Ash, J . E . and Hyde, E. editors, John Wiley & Sons, New York, (1975), pp 195 et seq. 3. Corey, E . J . and Wipke, W.T., Science, (1969), 166, 1978 4. Wipke, W.T., Dolata, D., Huber, M. and Buse, C., in this symposium volume, and references therein 5. Bersohn, M., Bull, Chem. Soc. Japan, (1972), 45, 1897 6. Bersohn, Μ., Esack, A. and Luchini, J., Computers & Chemistry, (1978), 2, 105 7. Gelernter, H.L., Sanders, A . F . , Larsen, C.L., Agarwal, K.K., Boivie, R.H., Spritzer, G.A., Searleman, J . E . , Science, (1977), 197, 1041 8. Kato, M., Kurihara, H., Kosugi, H., Watanabe, M., Asuka, S. and Yoshikoshi, Α., J . Chem. Soc. Perkin I, (1977), 2433 9. Arzoumanidis, G.G. and Rauch, F.C., Chem. Commun., (1973), 666 10. Stork, G. and Isobe, M., JACS, (1975), 97, 6260 11. Brown, H.C. and Krishnamurthy, S., JACS, (1972), 94, 7159 12. Corey, E.J., Q. Rev. Chem. Soc., (1971), 25, 455 13. Volkmann, R.A., Andrews, G.C. and Johnson, W.S., JACS, (1975), 97, 4777 Received June 8, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

17 CAMSEQ/M: A Microprocessor-Based Conformational Analysis System HERSCHEL J. R. WEINTRAUB

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch017

Department of Medicinal Chemistry and Pharmacognosy, School of Pharmacy and Pharmacal Sciences, Purdue University, West Lafayette, IN 47907

Conformational analysis is becoming a widely u t i l i z e d tool in drug design, molecular modeling, and the determination of structure-activity relationships. Of the many techniques pre­ sently available for conformational studies, c l a s s i c a l , empirical potential energy functions hold great promise in providing relatively inexpensive explorations of conformational hyperspace in various simulated solvent environments. An excellent example of the application of these classical techniques is embodied in theCAMSΕQSoftware System (1,2,3). Current computer technology has provided us with very power­ ful "stand alone", desk top microcomputers at very low cost. The a v a i l a b i l i t y of such a system which also provided interactive graphics capability prompted the development of "CAMSEQ/M". CAMSEQ employs classical-type empirically fitted potential energy functions which have been shown to accurately reproduce a large variety of experimental data (3-10). The conformational energy is determined using sets of pairwise potential energy functions, harmonic torsional correction terms, hydrogen-bonding terms, solvation and other free energy contributions. These terms have been described in detail elsewhere, but will be briefly reviewed at this time (3,11). Specific technical details of certain CAMSEQ and CAMSEQ/M implementations of these potential functions are included in this discussion. Steric, non-bonded, pairwise interactions are approximated by sets of Lennard-Jones 6-12 potential functions (3,11). Built­ -in parameters account for the interactions indicated in Table I. The user is free, however, to substitute particular sets of para­ meters with his own values (at run time) and even to change the nature of the function. For example, often a crystallographer feels more comfortable with a 6-9 type function rather than the b u i l t - i n 6-12; this change is very easily accomodated by simply specifying the "powers" to be used in the calculation. In this way, the system is very adaptable to the user's needs and can also be used for the development of new parameters. 0-8412-0521-3/79/47-112-353$05.00/0 © 1979 American Chemical Society

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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Table I Atom Types " B u i l t - i n " t o t h e CAMSEQ/M P o t e n t i a l F u n c t i o n s

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch017

C Cl H N 0 Ρ

(sp2) (aliphatic) (sp2) (s 2) P

C F H N 0 S

(sp3) (aromatic) (sp3) (sp3)

T y p i c a l l y , e l e c t r o s t a t i c i n t e r a c t i o n s a r e r e p r e s e n t e d by some form o f Coulomb's l a w - t y p e f u n c t i o n . I n t h i s t y p e o f c a l c u l a t i o n , t h e atoms i n t h e m o l e c u l e a r e a s s i g n e d a c h a r g e d i s t r i b u t i o n c o n s i s t i n g o f d i s c r e t e point charge approximations c e n t e r e d o n e a c h atom. O t h e r v a r i a t i o n s o f t h e s e s i m p l e f u n c t i o n s i n c l u d e e x p o n e n t i a l - t y p e a p p r o x i m a t i o n s (12) and v a r i a b l e d i e l e c t r i c a p p r o x i m a t i o n s ( 3 , 1 1 ) . The p o i n t c h a r g e a p p r o x i m a t i o n i s o f t e n d e t e r m i n e d by a b - i n i t i o o r s e m i - e m p i r i c a l m o l e c u l a r o r b i t a l c a l c u l a t i o n s . The u s e r may s e l e c t t h e p a r t i c u l a r f u n c t i o n a l r e p r e s e n t a t i o n used i n t h e c a l c u l a t i o n a s w e l l a s t h e p a r a m e t r i c form o f t h e f u n c t i o n . The v a r i a b l e d i e l e c t r i c f u n c t i o n i s r e p r e s e n t e d by a n a p p r o x i m a t i o n t o t h e r i g o r o u s l y d e r i v e d f u n c t i o n (3,11) f o r c o m p u t a t i o n a l e f f i c i e n c y . Since c l a s s i c a l - t y p e c a l c u l a t i o n s cannot i n t r i n s i c a l l y reproduce such e f f e c t s as atomic o r b i t a l i n t e r a c t i o n s , i t i s n e c e s s a r y t o a d j u s t t h e c o n f o r m a t i o n a l p o t e n t i a l e n e r g y terms to a c c u r a t e l y reproduce e x p e r i m e n t a l l y observed t o r s i o n a l b a r r i e r h e i g h t s . Harmonic t o r s i o n a l c o r r e c t i o n f u n c t i o n s a r e i n c o r p o ­ r a t e d i n t h e r e p e t o i r e o f c l a s s i c a l p o t e n t i a l e n e r g y terms i n o r d e r to e c o n o m i c a l l y s a t i s f y t h i s r e q u i r e m e n t . These f u n c t i o n s may be d e s c r i b e d i n s e v e r a l ways. S e t s o f p a r a m e t e r s may be g i v e n t o f i t a g e n e r a l p u r p o s e t o r s i o n a l c o r r e c t i o n term w h i c h includes provisions f o r d e s c r i b i n g cis/trans barriers. The g e n e r a l form o f t h i s e q u a t i o n i s N

E ( t o r ) = B a r r i e r l . [ A + B - C O S ( C χ+φΐ)]+Barrier2.[1-C0S(D

Χ+φ2)]

T h i s f u n c t i o n has n i n e a d j u s t a b l e p a r a m e t e r s and i s q u i t e e f f e c ­ t i v e i n d e s c r i b i n g most t o r s i o n a l c o r r e c t i o n t e r m s . A l t e r n a t i v e l y , a s e t o f d i s c r e t e v a l u e s may be d e f i n e d w h i c h are then used i n s t e a d o f a harmonic f u n c t i o n . L i n e a r i n t e r ­ p o l a t i o n i s t h e n used a s needed t o d e s c r i b e any m i s s i n g i n t e r ­ mediate v a l u e s . S i m i l a r l y , a two-dimensional t o r s i o n a l c o r ­ r e c t i o n t e r m may be u s e d when t h e o n e - d i m e n s i o n a l f u n c t i o n i s i n a d e q u a t e . An example o f s u c h a c a s e i s t h e g l y c o s y d i c l i n k a g e in dissaccharides (13). A phenomenon w h i c h must be a c c o u n t e d f o r i n many c o n f o r ­ mational problems i s t h a t o f the hydrogen-bonding e f f e c t . The g e n e r a l s t e r i c , non-bonded i n t e r a c t i o n p o t e n t i a l f u n c t i o n s and t h e e l e c t r o s t a t i c p o t e n t i a l a p p r o x i m a t i o n s do n o t , i n t r i n s i c a l l y , c o r r e c t l y account f o r the special p r o p e r t i e s encountered i n

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch017

17. WEINTRAUB

CAMSEQ/M

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hydrogen-bonded systems. F o r such c a s e s , CAMSEQ/M u t i l i z e s a s p e c i a l , e m p i r i c a l l y - f i t t e d , hydrogen-bonding p o t e n t i a l f u n c t i o n (14) . T h i s f u n c t i o n was d e v e l o p e d t o a c c u r a t e l y r e p r o d u c e e x p e r i m e n t a l l y o b s e r v e d h y d r o g e n - b o n d i n g e n e r g i e s f o r many s y s tems. An a n g u l a r d e p e n d e n c e term a c c o u n t s f o r g e o m e t r i c a l d e v i a t i o n s from t h e " i d e a l " , w h i l e a n o t h e r e m p i r i c a l l y - f i t t e d f u n c t i o n y i e l d s t h e observed hydrogen-bonding e n e r g i e s . The p r o d u c t o f t h e s e two f u n c t i o n s y i e l d s r e a s o n a b l e h y d r o g e n b o n d i n g energies f o r a l a r g e v a r i e t y o f molecular systems. S o l v a t i o n e f f e c t s a r e an important a s p e c t o f c o n f o r m a t i o n a l studies i n v o l v i n g b i o l o g i c a l l y important molecules. CAMSEQ/M u t i l i z e s a m o d i f i e d h y d r a t i o n s h e l l model t o a c c o u n t f o r t h e s e environmental e f f e c t s (3,9,11,15). Several simulated solvent e n v i r o n m e n t s may be c a l c u l a t e d . T h e s e i n c l u d e a q u e o u s , 1 - o c t a n o l (15) , m e t h a n o l , e t h a n o l , a c e t i c and f o r m i c a c i d ( 3 , 9 , 1 1 ) . Using t h i s method, t h e f r e e e n e r g y o f s o l v a t i o n o f t h e m o l e c u l a r s p e c i e s may be e s t i m a t e d . B e c a u s e o f t h e s t a t i s t i c a l n a t u r e o f t h e h y d r a t i o n s h e l l model, t h e dynamics o f t h e s o l v a t i o n e f f e c t a r e a c c o u n t e d f o r {9). By u s i n g c l a s s i c a l - t y p e e m p i r i c a l p o t e n t i a l e n e r g y f u n c t i o n s , accurate conformational c a l c u l a t i o n s which account f o r e x p e r i m e n t a l l y o b s e r v e d phenomena c a n be p e r f o r m e d . Geometry o p t i m i z a t i o n i s employed t o i m p r o v e t h e e f f i c i e n c y o f t h e c a l c u l a t i o n s . I n t h i s way, o n l y t h o s e atoms whose p o s i t i o n s change a s a function o f conformation a r e r e c a l c u l a t e d . A m u l t i - l e v e l ( m a j o r - m i n o r ) bond r o t a t i o n a l g o r i t h m has been d e v e l o p e d f o r CAMSEQ/M a n d i s c u r r e n t l y b e i n g i m p l e m e n t e d i n CAMSEQ. U s i n g t h i s scheme, two l e v e l s o f i m p o r t a n c e a r e a s s i g n e d t o t h e t o r s i o n a l bond r o t a t i o n s . T h e s e may be s i m p l y d e s c r i b e d as " m a j o r " r o t a t i o n s , o r t h o s e i n v o l v i n g backbone o r o t h e r m a j o r b o n d s , a n d " m i n o r " r o t a t i o n s i n v o l v i n g m e t h y l g r o u p s , amine groups o r o t h e r s i d e c h a i n r o t a t i o n s . The a l g o r i t h m was d e s i g n e d t o work i n e i t h e r s e q u e n t i a l s c a n , random s c a n , o r m u l t i d i m e n s i o n a l m i n i m i z a t i o n modes. T h e t e c h n i q u e may be c l o s e l y compared t o a q u a n t i t a t i v e model b u i l d i n g e x e r c i s e . I n m o l e c u l a r model b u i l d i n g , t h e " m a j o r " bonds a r e a d j u s t e d t o t h e i r a p p r o x i m a t e d e s i r e d p o s i t i o n s , and t h e m i n o r groups a r e t h e n " f i n e - t u n e d " t o p o s i t i o n s w h i c h m i n i m i z e u n f a v o r a b l e c l o s e c o n t a c t s . O t h e r c o n f o r m a t i o n s a r e examined u n t i l t h e d e s i r e d s t r u c t u r e i s c o n s t r u c t e d . I n a s i m i l a r manner, CAMSEQ/M a d j u s t s t h e "major" t o r s i o n a n g l e s a c c o r d i n g t o t h e s e l e c t e d s e a r c h mode ( p r o t o t y p e v e r s i o n s a r e l i m i t e d t o s e q u e n t i a l s c a n modes, b u t random and m u l t i - d i m e n s i o n a l m i n i m i z a t i o n p r o c e d u r e s a r e c u r r e n t l y b e i n g i m p l e m e n t e d ) and f o l l o w s t h i s by a l i m i t e d s e a r c h f o r l o w e n e r g y c o n f o r m e r s f o r each o f t h e " m i n o r " t o r s i o n a n g l e s . Upon s e t t i n g t h e l a t t e r bonds t o t h e i r l o w e s t e n e r g y p o s i t i o n s , t h e t o t a l conformational energy i s determined. While t h i s procedure i n c r e a s e s t h e c a l c u l a t i o n time p e r c o n f o r m a t i o n a l s t a t e , i n g e n e r a l , t h e t o t a l search o f conformational hyperspace i s c o n s i d e r a b l y more r a p i d and e c o n o m i c a l , a s f e w e r c o n f o r m a t i o n a l

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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s t a t e s a r e ( f u l l y ) examined. The s a v i n g s a c h i e v e d b y t h i s method r e s u l t from t h e t e c h ­ n i q u e s e m p l o y e d . The c a l c u l a t i o n o f t h e g e o m e t r i e s and e n e r g i e s a s s o c i a t e d w i t h r o t a t i o n s a b o u t t h e "minor" bonds a r e v e r y r a p i d . T h e s e c a l c u l a t i o n s i n v o l v e o n l y t h e atoms w h i c h have moved a s a r e s u l t o f t h e "minor" r o t a t i o n s . T h e p a i r w i s e e n e r g y terms i n v o l v e o n l y o r d e r Ν c a l c u l a t i o n s (where Ν i s t h e number o f atoms i n t h e m o l e c u l e ) a s compared t o o r d e r N f o r t h e c a l c u l a t i o n o f one c o n f o r m a t i o n a l s t a t e . Thus t h e "minor" r o t a t i o n c a l c u l a t i o n s s e r v e o n l y t o d e s c r i b e t h e optimum p o s i t i o n s o f t h e r e s p e c t i v e atoms. Since the efficiency o f multidimensional minimization schemes i s d e p e n d e n t o n t h e number o f d e g r e e s o f r o t a t i o n a l f r e e d o m , t h e s e p a r a t i o n o f "major" from "minor" t o r s i o n a l r o t a ­ t i o n s should d r a m a t i c a l l y enhance t h e speed o f convergence o f t h e s e r o u t i n e s . O f c o u r s e , " n o r m a l " r o t a t i o n a l methods may be a p p l i e d s i m p l y by s p e c i f y i n g no "minor" o r s e c o n d a r y r o t a t i o n parameters. The p r e c e e d i n g d i s c u s s i o n has b r i e f l y d e s c r i b e d t h e p o t e n ­ t i a l f u n c t i o n s a n d g e o m e t r y d e t e r m i n a t i o n a l g o r i t h m s employed i n CAMSΕQ and p a r t i c u l a r l y i n CAMSEQ/M. T h e " b a t c h " v e r s i o n o f CAMSEQ c u r r e n t l y i n u s e i s t o t a l l y c o m p a t i b l e w i t h CAMSEQ/M. CAMSEQ/M c a n be i n t e r f a c e d ( v i a a c o m m u n i c a t i o n s l i n k ) t o a h o s t c o m p u t e r f o r more l e n g t h y c a l c u l a t i o n s where s p e e d i s a r e q u i r e ­ ment ( r a t h e r t h a n e c o n o m y ) . CAMSEQ/M has been d e v e l o p e d a s a n a l t e r n a t i v e means f o r t h e determination o f t h e conformational p o t e n t i a l energy s e r f a c e s o f m o l e c u l e s . The study o f b i o l o g i c a l l y important molecules l e d t o t h e o r i g i n a l d e v e l o p m e n t o f CAMSEQ (1,3-10). More r e c e n t d e v e l o p m e n t s have l e d t o a n i n t e r a c t i v e v e r s i o n m o d i f i e d b y H o p f i n g e r a n d P o t e n z o n e (2) f o r t h e NIH-EPA-Chemical I n f o r m a t i o n System ( C I S ) ( Ή 5 ) . T h i s v e r s i o n ( d e s i g n a t e d a s CAMSEQ-II) r e f l e c t e d more c u r r e n t s t a t e - o f - t h e - a r t c o m p u t e r t e c h n o l o g y a n d requires the use o f a moderately l a r g e mini-computer. Some o f i t s f e a t u r e s i n c l u d e t h e a v a i l a b i l i t y o f l a r g e d a t a bases c o n ­ t a i n i n g many t h o u s a n d s o f m o l e c u l a r s t r u c t u r e s , a n d t h e c o n ­ v e n i e n c e o f " c o n v e r s a t i o n a l mode" i n p u t s e q u e n c e s t o a i d t h e user i n data p r e p a r a t i o n . The a v a i l a b i l i t y o f m i c r o p r o c e s s o r - b a s e d i n t e r a c t i v e com­ p u t e r g r a p h i c s d e v i c e s a n d r a p i d a c c e s s d i s k s t o r a g e has p r o v i d e d t h e CAMSEQ/M s y s t e m w i t h many o f t h e f e a t u r e s o f t h e NIH-EPA-CIS (on a s m a l l e r s c a l e , o f c o u r s e ) and i n a d d i t i o n , p r o v i d e s "nocost", local computational f a c i l i t i e s . In p r a c t i c e , i t i s r a r e l y n e c e s s a r y t o m a i n t a i n h u n d r e d s o f d i v e r s e m o l e c u l a r s t r u c t u r e s f o r immediate a c c e s s . Conformation­ a l s t u d i e s a r e g e n e r a l l y p e r f o r m e d on a s m a l l c o n g e n e r i c s e r i e s o f m o l e c u l e s w h i c h , o f c o u r s e , s h o u l d be i m m e d i a t e l y a v a i l a b l e . CAMSEQ/M p r o v i d e s f o r t h e l o c a l s t o r a g e o f s e v e r a l hundred s t r u c t u r e s . I f a d d i t i o n a l s t r u c t u r e s a r e r e q u i r e d , t h e NIH-EPACIS c a n be l i n k e d t o t h e l o c a l t e r m i n a l v i a t e l e p h o n e

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch017

2

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch017

17.

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c o m m u n i c a t i o n s and t h e n e c e s s a r y s t r u c t u r e s l o c a t e d and " s e n t " t o t h e t e r m i n a l . T h e s e f i l e s o f new s t r u c t u r e s may t h e n be s a v e d f o r f u t u r e u s e . T h e r e f o r e , CAMSEQ/M i s d e s i g n e d t o s u p p l e m e n t t h e NIH-EPA-CIS b y p r o v i d i n g l o c a l p r o c e s s i n g power, r e l i e v i n g t h e l a t t e r s y s t e m f o r d a t a base m a n i p u l a t i o n r a t h e r t h a n t i m e consuming c o n f o r m a t i o n a l energy c a l c u l a t i o n s . CAMSEQ/M was d e v e l o p e d a r o u n d a T e k t r o n i x 4051 Microcomputer G r a p h i c s S y s t e m . The hardware r e q u i r e d i n c l u d e s t h e b a s i c 4051 m i c r o c o m p u t e r w i t h a minimum o f 16k b y t e s o f memory (32k i s recommended), a " j o y s t i c k " g r a p h i c a l i n p u t d e v i c e , and a m a t r i x f u n c t i o n p a c k a g e ( i n a r e a d - o n l y memory f i r m w a r e p a c k ) . A v a s t l y more v e r s a t i l e s y s t e m r e q u i r e s t h e a d d i t i o n o f a f i l e manager/ d i s k s y s t e m . In o r d e r t o communicate w i t h t h e NIH-EPA-CIS o r another "host" computer, a communications i n t e r f a c e i s n e c e s s a r y . The t o t a l hardware c o s t i s a p p r o x i m a t e l y $17,000. T a b l e I I o u t l i n e s t h e r e q u i r e d h a r d w a r e . The 4051 u t i l i z e s a d i r e c t v i e w s t o r a g e d i s p l a y w h i c h does n o t employ a s e l e c t i v e e r a s e f e a t u r e . T h e r e f o r e , i t i s necessary to r e p l o t the screen f r e q u e n t l y i n o r d e r t o remove unwanted i n f o r m a t i o n . T h i s h a n d i c a p i s t h e p r i c e one must pay f o r low c o s t , b u t q u i t e s o p h i s t i c a t e d c o m p u t e r g r a p h i c s f e a t u r e s , and does n o t pose any m a j o r problems i n CAMSEQ/M. Table II Hardware Item T e k t r o n i x 4051 M i c r o c o m p u t e r A d d i t i o n a l 16K memory M a t r i x f u n c t i o n ROM pack Joystick input device

w/16k

memory

F i l e manager/disk system Communications i n t e r f a c e Upon t u r n i n g on t h e s y s t e m and i n i t i a t i n g CAMSEQ/M, t h e u s e r i s shown a "menu" from w h i c h t o s e l e c t t h e p a r t i c u l a r t a s k t o be performed. Figure 1 i l l u s t r a t e s the screen d i s p l a y a f t e r the " c r y s t a l l o g r a p h i c c o o r d i n a t e " i n p u t f e a t u r e has been s e l e c t e d . As can be s e e n , t h e program prompts t h e u s e r f o r t h e v a r i o u s u n i t c e l l p a r a m e t e r s . A t n e a r l y any p o i n t , a " q u e s t i o n mark" may be t y p e d , and CAMSEQ/M w i l l h i g h l i g h t t h e a p p r o p r i a t e i n f o r m a t i o n on t h e s c r e e n t o a s s i s t t h e u s e r i n d e t e r m i n i n g what he s h o u l d do. CAMSEQ/M p r o v i d e s t h e u s e r w i t h t h e c a p a b i l i t y t o i n p u t c o m p l e t e m o l e c u l a r s t r u c t u r e s from t h e i n t e r n a l ( d i s k ) d a t a b a s e , to i n p u t c a r t e s i a n o r c r y s t a l l o g r a p h i c c o o r d i n a t e s , o r t o use a " j o y s t i c k " c o n t r o l l e d m o d e l - b u i l d i n g s y s t e m . In a d d i t i o n , a m o l e c u l e may be c o n s t r u c t e d from one o r more s u b s t r u c t u r e s w i t h s u b s t i t u e n t s attached using the j o y s t i c k model-builder r o u t i n e s . Data i n p u t i s t h e r e f o r e q u i t e f l e x i b l e , and t h e u s e r i s g u i d e d t h r o u g h e v e r y s t e p by t h e p r o g r a m . C o n t i n u i n g w i t h t h e example d e p i c t e d i n F i g u r e 1, t h e u s e r

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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RESTART

CAHSEQvH I MICROPROCESSOR-BASED CONFORMATIONAL ANALYSIS SYSTEM

DO

YOU H A U E

A JOYSTICK

?

INPUT COORDS CARTESIAN

> θ ENTER OPTION NAME (OR COMMAND BY PRESSING USER KEY " 1 " ) · a t o n s i z e ENTER NUMBER OF DATA ITEMS: 4 THE SPECIFIED OPTION REQUIRES THAT THE FOLLOWING 4 DATA ITEMS BE SUPPLIED. RADIUS RADIUS RADIUS RADIUS

OF OF OF OF

M

M

"H C(SP2) "C(SP3> N(SP2>" M

M

M

> > > >

1.1 1.4 1.38 1.44

Figure 6. CAMSEQ/M provides a brief description of each input item for the selected options. A full description of the option is available by pressing the "help" key (user key 10 on the Tektronix keyboard) and entering the option name.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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bond r o t a t i o n d a t a , t h e u s e r i s a s k e d i f he w i s h e s t o d e s c r i b e a reference conformation. I f "REFERENCE" was s p e c i f i e d p r e v i o u s l y , t h e u s e r w i l l be prompted f o r t h e a p p r o p r i a t e i n f o r m a t i o n at t h i s t i m e w i t h o u t t h e q u e r y . I n t h i s manner, even i f o n e f o r g e t s t o s e l e c t a n o p t i o n i n a d v a n c e , CAMSEQ/M p r o v i d e s a r e m i n d e r t h a t t h e o p t i o n i s a v a i l a b l e . I f u s i n g CAMSEQ/M a s a " s t a n d - a l o n e " computer, i t i s n o t even necessary t o s p e c i f y t h e " s e l e c t o p t i o n s " f e a t u r e d e p i c t e d o n t h e menu i n F i g u r e 1. One need m e r e l y p r e s s t h e k e y l a b e l e d " p e r f o r m c o n f o r m a t i o n a l s e a r c h " , and t h e a p p r o p r i a t e o p t i o n s w i l l be r e q u e s t e d . I n d i v i d u a l c o n f o r m a t i o n a l s t a t e s may be e x a m i n e d by s p e c i f y i n g " s i n g l e c o n f o r m a t i o n " when prompted f o r t h e bond r o t a t i o n parameters. T h e c o o r d i n a t e s f o r t h i s c o n f o r m e r may be s a v e d and t h e r e s u l t a n t s t r u c t u r e may be d i s p l a y e d . The u s e r w i l l t h e n be prompted f o r a n o t h e r s i n g l e c o n f o r m e r o r f o r a n e n e r g y c a l c u l a t i o n . I n " s i n g l e c o n f o r m a t i o n " mode, i n d i v i d u a l e n e r g y t e r m s may be i n s p e c t e d . Thus t h e t o t a l , s t e r i c , e l e c t r o s t a t i c , o r o t h e r e n e r g y t e r m s c a n be d e t e r m i n e d , o r t h e i n t e r a c t i o n e n e r g y between a g i v e n p a i r o f atoms may be computed. The l a t t e r p a i r w i s e e n e r g y c o n t r i b u t i o n i s a v a i l a b l e o n l y i n t h e " s i n g l e c o n f o r m a t i o n " mode. A u t o m a t i c s e a r c h e s o f c o n f o r m a t i o n a l h y p e r s p a c e may be r e q u e s t e d u s i n g t h e m u l t i - l e v e l bond r o t a t i o n a l g o r i t h m d e s c r i b e d a b o v e . A s e l e c t i o n i s made f o r a u n i f o r m s e q u e n t i a l s c a n , a random s c a n , o r a m u l t i - d i m e n s i o n a l m i n i m i z a t i o n s e a r c h o f t h e c o n f o r m a t i o n a l e n e r g y s u r f a c e . (As i n d i c a t e d a b o v e , p r o t o t y p e v e r s i o n s o f CAMSEQ/M p r o v i d e o n l y t h e s e q u e n t i a l s c a n mode.) The " m a j o r " o r p r i m a r y bond r o t a t i o n s a r e t h e n d e s c r i b e d , f o l lowed b y t h e s e c o n d a r y , o r "minor" r o t a t i o n a l i n f o r m a t i o n . B a s e d on t h e o p t i o n s s p e c i f i e d , CAMSEQ/M may r e q u e s t a d d i t i o n a l i n f o r m a t i o n r e g a r d i n g t h e energy parameters t o u s e , t h e s o l v e n t e n v i r o n m e n t s t o be s i m u l a t e d , and o t h e r p e r t i n e n t i n f o r m a t i o n r e g a r d i n g t h e c o n f o r m a t i o n a l a n a l y s i s t o be p e r f o r m e d . The u s e r i s t h e n g i v e n t h e o p p o r t u n i t y t o a s s e m b l e a b a t c h CAMSEQ d a t a s e t t o be s e n t t o a n a l t e r n a t e c o m p u t e r . T h i s f e a t u r e a s s e m b l e s a l l d a t a a c c u m u l a t e d i n t o t h e form o f a CAMSEQ run deck and saves t h e i n f o r m a t i o n on a d i s k f i l e . A l t e r n a t i v e l y , CAMSEQ/M b e g i n s t h e c o n f o r m a t i o n a l a n a l y s i s t a s k , s a v i n g r o t a t i o n a l a n d e n e r g y i n f o r m a t i o n on a d i s k f i l e . Data a n a l y s i s o p t i o n s i n c l u d e t h e p r e p a r a t i o n o f i s o e n e r g y c o n t o u r maps (CMAPS), l i n e a r e n e r g y v s . r o t a t i o n a n g l e p l o t s (LINPLOT) and t a b l e s o f l o c a l e n e r g y m i n i m a , s t a t i s t i c a l t h e r m o d y n a m i c p r o b a b i l i t i e s , and e n t r o p y terms t o e n a b l e t h e reporting o f "free" energies i n addition t o "conformational" energies. The i s o e n e r g y c o n t o u r maps a r e p l o t t e d o n e " l e v e l l i n e " a t a t i m e . The u s e r s p e c i f i e s t h e e n e r g y l e v e l t o be p l o t t e d ( s a y 1 K c a l / m o l e above t h e g l o b a l e n e r g y minimum), and a l l r e g i o n s with energy l e s s than o r equal t o t h a t energy a r e i n d i c a t e d by an i s o e n e r g y c o n t o u r l i n e . P r o v i s i o n i s made f o r l a b e l i n g o f

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the

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contour lines using the j o y s t i c k . In o r d e r t o d e t e r m i n e t h e s t a t i s t i c a l t h e r m o d y n a m i c p r o b a b i l i t i e s and e n t r o p i e s f o r t h e c o n f o r m a t i o n a l energy s u r face, a s e t o f "dots" i s plotted i n d i c a t i n g the angular values o f the s e t o f conformers which d e f i n e t h e s u r f a c e . The j o y s t i c k c u r s e r c o n t r o l i s used t o s e l e c t t h e s e t o f c o n f o r m e r s w h i c h o c c u p y a g i v e n l o w e n e r g y r e g i o n . The c h o s e n " d o t s " a r e r e p l a c e d by " a s t e r i s k s " ( t o a v o i d d u p l i c a t i o n ) and t h e p r o b a b i l i t y and e n t r o p y t e r m s a r e t a b u l a t e d . T a b l e s o f p r o b a b i l i t i e s a n d e n t r o p i e s may a l s o be p r o d u c e d . The l i n e a r e n e r g y v s . r o t a t i o n a n g l e p r o f i l e s a r e p r o d u c e d d i r e c t l y from t h e c o n f o r m a t i o n a l e n e r g y d a t a f i l e . F i g u r e 7a shows a r e p r e s e n t a t i v e sample o f a c o n f o r m a t i o n a l i s o e n e r g y c o n t o u r map. F i g u r e 7b i l l u s t r a t e s t h e p r o c e d u r e f o r c a l c u l a t i n g p r o b a b i l i t i e s and e n t r o p i e s . A t y p i c a l l i n e a r p l o t o f energy v s . r o t a t i o n angle i s d e p i c t e d i n f i g u r e 7c. C o m p l e t e c o n f o r m a t i o n a l a n a l y s e s may be p e r f o r m e d u s i n g CAMSEQ/M. The f i g u r e s i n t h i s r e p o r t were p r e p a r e d d i r e c t l y from t h e s c r e e n d i s p l a y ( p r o d u c e d by a T e k t r o n i x h a r d c o p y d e v i c e ) . P h o t o g r a p h s may a l s o be made from t h e s c r e e n d i s p l a y . C u r r e n t e f f o r t s i n t h e d e v e l o p m e n t o f t h e CAMSEQ/M s y s t e m i n c l u d e t h e i n t e r f a c i n g o f a l o w - c o s t m i c r o c o m p u t e r t o t h e 4051 to handle t h e a c t u a l c o n f o r m a t i o n a l search and energy c a l c u l a t i o n . T h i s would f r e e t h e g r a p h i c s t e r m i n a l f o r o t h e r general purpose computing tasks i n c l u d i n g t h e set-up o f a d d i t i o n a l molecules f o r conformational study. Conceptually, banks o f t h e s e l o w - c o s t m i c r o c o m p u t e r s c o u l d be l i n k e d t o a s i n g l e 4051 t o p r o v i d e a v e r y e f f i c i e n t c o n f o r m a t i o n a l a n a l y s i s device. T h e r e a r e many a p p l i c a t i o n s o f c o n f o r m a t i o n a l a n a l y s i s i n drug design and m o l e c u l a r modeling. Comparisons o f t h e c o n f o r m a t i o n a l e n e r g y s u r f a c e s and r o t a t i o n a l e n e r g y p r o f i l e s w i t h i n c o n g e n e r i c s e r i e s o f compounds c a n p r o v i d e v a l u a b l e information f o r the determination o f s t r u c t u r e - a c t i v i t y r e l a t i o n s h i p s . Common l o w e n e r g y r e g i o n s o r s p a t i a l c h a r a c t e r i s t i c s among a c t i v e o r i n a c t i v e members o f a s e r i e s o f m o l e c u l e s can l e a d t o a n u n d e r s t a n d i n g o f some o f t h e p r o p e r t i e s w h i c h a r e important f a c t o r s i n t h e observed a c t i v i t y o r i n a c t i v i t y o f those molecules. There a r e s e v e r a l conformation-dependent drug design methods i n u s e . T h e u s e o f r i g i d a n a l o g s t o probe r e c e p t o r s i s one o f t h e s e . Armed w i t h a s e r i e s o f c o n f o r m a t i o n a l l y r e s t r i c t e d a n a l o g s , o n e assumes t h a t o n l y t h o s e c o n g e n e r s t h a t " f i t " t h e r e c e p t o r w i l l be a c t i v e . When s e v e r a l s u c h compounds a r e i n v e s t i g a t e d , t h e g e n e r a l s p a t i a l and e l e c t r o n i c p r o p e r t i e s o f t h e r e c e p t o r c a n o f t e n be d i s c e r n e d . We have been a p p l y i n g t h i s technique t o a s e r i e s o f phenethylamine d e r i v a t i v e s r e l a t e d t o the hallucinogen 2,5-dimethoxy-4-methylphenylisopropylamine (DOM, S T P ) . A c o m p a r i s o n o f t h e a l l o w e d c o n f o r m a t i o n a l s t a t e s and s t e r i c p r o p e r t i e s o f t h e s e m o l e c u l e s w i t h s i m i l a r d a t a

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A

ENTER LEUEL L I N E VALUE 1

2

3

Β

ENTER LEUEL L I N E VALUE 1

2

3

5

β

C

Figure 7. (A) CAMSEQ/M produced conformational isoenergy contour map; (B) procedure for calculating probabilities and entropies; (C) plot of energy vs. rotation angle

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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f o r DOM has been v e r y u s e f u l i n d e f i n i n g p r o b a b l e r e c e p t o r c o m p l i m e n t a r i t y ( 9 , 1 0 ) . T h e s e s t u d i e s have l e d t o i d e a s f o r new compounds t o s t u d y w h i c h a r e now b e i n g s y n t h e s i z e d . CAMSEQ a n a l y s i s o f t h e s e new a n a l o g s , and c o r r e l a t i o n w i t h b i o l o g i c a l a c t i v i t y w i l l s e r v e as " i n p u t " t o r e f i n e f u r t h e r p r o p o s e d receptor topography. An e x c e l l e n t d i s c u s s i o n o f t h e a p p l i c a t i o n o f c o n f o r m a t i o n a l methods may be f o u n d i n r e f e r e n c e s T_9 and 20. R e c e p t o r m a p p i n g and t h e r i g i d a n a l o g s d i s c u s s e d above a r e b u t two o f t h e a p p l i c a t i o n s w h i c h CAMSEQ/M i s d e s i g n e d t o h a n d l e . By u s i n g CAMSEQ/M a s a p r e p r o c e s s o r f o r d a t a i n p u t a n d u s i n g t h e companion b a t c h CAMSEQ f o r t h e c o n f o r m a t i o n a l s t u d y , s e m i - e m p i r i c a l m o l e c u l a r o r b i t a l methods may be employed t o examine p r e s e l e c t e d r e g i o n s o f c o n f o r m a t i o n a l h y p e r s p a c e . As r e p o r t e d p r e v i o u s l y , CAMSEQ (1) has been i n t e r f a c e d w i t h CNDO/2, PCILO, and o t h e r w i d e l y used MO t e c h n i q u e s . CAMSEQ/M c a n t h e r e f o r e p r o v i d e a s i m p l i f i e d d a t a i n p u t and d a t a a n a l y s i s p a c k a g e f o r c l a s s i c a l e m p i r i c a l p o t e n t i a l energy c a l c u l a t i o n s as well as semiempirical molecular orbital studies. A c k n o w l e d g e m e n t s : S u p p o r t from t h e U.S. P u b l i c H e a l t h S e r v i c e (GM 25142) and t h e Purdue C a n c e r C e n t e r i s a c k n o w l e d g e d . Literature Cited: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.

Weintraub, H.J.R.; Hopfinger, A.J. Int. J . Quantum Chem., 1975, QBS2, 203. Potenzone, R. J r . ; Cavicchi, E . ; Weintraub, H.J.R.; Hopfinger, A . J . Computers and Chem., 1977, 1, 187. Weintraub, H.J.R. Ph.D. Dissertation, Case Western Reserve University, Cleveland, Ohio, 1975. Weintraub, H.J.R.; Hopfinger, A . J . J . Theor. B i o l . , 1973, 41, 53. Weintraub, H.J.R.; Hopfinger, A . J . , in "Molecular and Quantum Pharmacology", Bergmann, E . ; Pullman, B., Eds., D. Reidel, Dordrecht, Holland, 1974; p. 131. Weintraub, H.J.R.; Tsai, M.D.; Byrn, S.R.; Chang, C.-j.; Floss, H.G. Int. J . Quantum Chem., 1976, QBS3, 99. Weintraub, H.J.R. Int. J . Quantum Chem., 1977, QBS4, 111. Tsai, M.D.; Weintraub, H.J.R.; Byrn, S.R.; Chang, C.-j.; Floss, H.G. Biochemistry, 1978, 17, 3183. Weintraub, H.J.R.; Nichols, D.E. Int. J. Quantum Chem., 1978, QBS5, 321. Nichols, D.E.; Weintraub, H.J.R.; Pfister, W.R.; Yim, G.K.W., in "NIDA Research Monograph Series", Barnette, G.; Trsic, M.; Willette, R., Eds., 1978, 22, 70. Hopfinger, A.J. "Conformational Properties of Macromolecules", Academic Press, New York, 1973. Hesselink, F.T.; Ooi, T . ; Scheraga, H.A. Macromolecules, 1973, 6 (4), 541.

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370 13. 14. 15. 16. 17.

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18. 19. 20.

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Potenzone, R., Jr., M.S. Thesis, Case Western Reserve University, Cleveland, Ohio, 1975. Weintraub, H . J . R . , presented at 1979 Sanibel Symposium, Palm Coast, Florida, March, 1979. Manuscript in preparation Hopfinger, A.J.; Battershell, R.D. J . Med. Chem., 1976, 19 (5), 569. Heller, S.R.; Milne, G.W.A.; Feldman, R . J . Science, 1977, 195 (4275), 253. Sutton, L . E . Chem. Soc., Special Publication No. 11, 1958; Supplement No. 18, 1965. Jain, S . C . ; Tsai, C . - c . ; Sobell, H.M. J. Mol. Biol., 1977, 114, 317. Martin, Y . C . , "Quantitative Drug Design, A Critical Introduction:, Dekker, New York, 1978. Richards, W.G., "Quantum Pharmacology", Butterworths, London, 1977.

Received June 8, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

18 Beyond the 2-D Chemical Structure

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch018

N. C. COHEN Centre de Recherches ROUSSEL-UCLAF, 102 Route de Noisy, 93230 Romainville, France

The s p e c t a c u l a r d e v e l o p m e n t o f t h e QSAR t h e o r i e s has domin a t e d t h e r e c e n t e v o l u t i o n o f d r u g - d e s i g n , and t h e c o n d i t i o n s f o r t h e u s e o f t h e s e t h e o r i e s a r e now w e l l e s t a b l i s h e d . Being cons t r u c t e d on a p a r t i c u l a r c h e m i c a l f o r m u l a , w i t h an i m p l i c i t common i n v a r i a n t c h e m i c a l s k e l e t o n , t h e s e methods a r e n o t a l w a y s a b l e t o go beyond t h e c h e m i c a l f r a m e o f t h e p a r t i c u l a r f a m i l y s t u d i e d . The r e c e n t a d v a n c e o f m o l e c u l a r b i o l o g y has w i d e n e d t h e c l a s s i c a l h o r i z o n s o f d r u g r e s e a r c h w h i c h has been c a r r i e d o u t u n t i l now on m a i n l y t w o - d i m e n s i o n a l l i n e s , a n d b a s e d on t h e s y n t h e s i s o f c h e m i c a l a n a l o g s o f known compounds. T h i s a d v a n c e i s due t o t h e discovery o fthe three dimensional s p e c i f i c i t y o f molecular i n t e r a c t i o n s w h i c h i s a f u n d a m e n t a l key t o t h e u n d e r s t a n d i n g o f l i f e processes. The c o n c e p t s o f m o l e c u l a r r e c o g n i t i o n a n d d i s c r i m i n a t i o n c o n s i d e r e d i n t h e l i g h t o f d r u g r e s e a r c h a l l o w one t o go beyond t h e c l a s s i c a l d r u g m a n i p u l a t i o n and o p t i m i z a t i o n . Geometr i c a l and a s s o c i a t e d e l e c t r o n i c p r o p e r t i e s a r e o f g r e a t importance t o t h i s new a p p r o a c h . New T r e n d s F o r t h e c o n c e p t i o n o f new m o l e c u l a r s t r u c t u r e s i t i s f i r s t n e c e s s a r y t o be a b l e t o e v a l u a t e t h e g e o m e t r i c a l p r o p e r t i e s o f reference molecules. T h e o r e t i c a l c a l c u l a t i o n s o f conformations a r e now a c c u r a t e enough s o t h a t t h i s p o i n t c a n be t a k e n as r e a d even f o r m o l e c u l e s n o t y e t s t u d i e d e x p e r i m e n t a l l y . W i t h t h e a i d o f t h e s e now c l a s s i c a l t e c h n i q u e s t h e d r u g - d e s i g n e r c a n go f u r t h e r and a d d r e s s h i m s e l f t o t h e t h r e e f o l l o w i n g f u n d a m e n t a l i t e m s : 1-

How t o r e v e a l , what t h r e e d i m e n s i o n a l s t r u c t u r a l e n t i t i e s (pharmacophore) a r e r e s p o n s i b l e f o r t h e b i o l o g i c a l p r o p e r t i e s o f a known a c t i v e compound, a n d what c o u l d be t h e a c t i v e c o n f o r m a t i o n o f t h i s compound, i f more t h a n one c o n f o r m e r i s p r o b a b l e .

2.

How t o e v a l u a t e t o what e x t e n t d i f f e r e n t m o l e c u l e s c a n 0-8412-0521-3/79/47-112-371$05.00/0 ©

1979 A m e r i c a n C h e m i c a l Society

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

372

COMPUTER-ASSISTED DRUG DESIGN

m i m i c t h e s p a t i a l a r r a n g e m e n t o f atoms o f a known a c t i v e compound o r i t s p u t a t i v e p h a r m a c o p h o r e . 3.

We purpose

How t o c o n c e i v e o f a method f o r d e s i g n i n g o r i g i n a l chemic a l compounds w h i c h c o n f o r m t o t h e d e s i r e d r e q u i r e m e n t s . have d e v e l o p e d a c o m p u t e r p r o g r a m MIMETIC-GEMO, t h e o f w h i c h i s t o be o f some h e l p i n a n s w e r i n g p o i n t s 1

and

2.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch018

Mimetic-Gemo T h i s c o m p u t e r p r o g r a m i s a b l e t o compare t h e m o l e c u l a r g e o m e t r i e s o f d i f f e r e n t m o l e c u l e s w i t h o u t any r e s t r i c t i o n s on t h e i r r e l a t i v e chemical s t r u c t u r e . The o n l y i m p l i c i t a s s u m p t i o n i s t h a t t h e compounds s t u d i e d a r e s u p p o s e d t o a c t b i o l o g i c a l l y by t h e same mechanism o f a c t i o n . The p r o g r a m i s a b l e t o compare a s e t o f a t l e a s t two m o l e c u l e s ( t h e a c t u a l v e r s i o n i s programmed f o r a maximum o f n = 6 m o l e c u l e s ) . The m o l e c u l e s a r e c o n s i d e r e d as f r e e t o move and t o m o d i f y t h e i r g e o m e t r i e s , p r o v i d e d t h a t t h e g l o b a l d e f o r m a t i o n o f each m o l e c u l e does n o t i n c r e a s e t h e t o t a l m o l e c u l a r e n e r g y by more t h a n a p r e - e s t a b l i s h e d amount ( i . 9 . 10-15 kcal/mole). A t t h e b e g i n n i n g o f t h e c a l c u l a t i o n s an i n i t i a l p o s i t i o n i s c h o s e n f o r each m o l e c u l e , t o g e t h e r w i t h t h e r e l a t i v e o r i e n t a t i o n s one t o t h e o t h e r , t h e t o t a l sum o f m o l e c u l e s f o r m i n g a set of n overlapping molecular geometries. The p a r a m e t e r used t o c h a r a c t e r i z e t o what e x t e n t t h e "mimetism" i s a c h i e v e d i s S^. t h e t o t a l exposed m o l e c u l a r a r e a o f t h i s set of overlapping molecules. The a i m o f t h e c a l c u l a t i o n s i s t o f i n d what a r e t h e g e o m e t r i e s o f each o f t h e n m o l e c u l e s w h i c h lead to a minimal value of S j . I n MIMETIC-GEMO t h e m o l e c u l a r e n e r g i e s and d e f o r m a t i o n s a r e c a l c u l a t e d u s i n g a p r e v i o u s l y d e s c r i b e d c o m p u t e r p r o g r a m (1J, w h i l e t h e m i n i m i z a t i o n i s c o n d u c t e d w i t h a s t a n d a r d r o u t i n e [2J • When t h e minimum i s r e a c h e d , i t i s i n t e r e s t i n g t o know f o r each molecule: - what i s i t s f i n a l g e o m e t r y and t h e c o r r e s p o n d i n g m o l e c u l a r energy, - what a r e t h e o v e r l a p p i n g and t h e n o n - o v e r l a p p i n g m o i e t i e s o f one compound r e l a t i v e t o t h e o t h e r s . I t i s a l s o u s e f u l t o a s c e r t a i n what a r e t h e g e n e r a l geometf e a t u r e s common t o t h e w h o l e s e t o f m o l e c u l e s s t u d i e d . The p r i n c i p l e o f m i n i m i z i n g t h e t o t a l e x p o s e d m o l e c u l a r s u r f a c e a r e a S j p a r a m e t e r i s a rough b u t p r a c t i c a l i n d e x . B e t t e r t h a n t h e manual m a n i p u l a t i o n o f a p p r o x i m a t e m o l e c u l a r m o d e l s t h i s c r i t e r i o n can be a p o w e r f u l t o o l f o r r e v e a l i n g t h e 3-D m i m e t i s m between s e v e r a l m o l e c u l e s . An example t o i l l u s t r a t e t h e rical

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

18.

COHEN

Beyond

the 2-D

Chemical

p o s s i b i l i t i e s o f t h i s approach

Structure

i s given

373

below.

Example

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch018

I n o u r r e s e a r c h g r o u p a p o t e n t h y p o l i p i d e m i c a g e n t has been f o u n d (compound I I I ) (3) w h i c h i s a c t i v e as t r e l o x i n a t e ( I I ) (4J and c l o f i b r a t e (I_) (J5) i n l o w e r i n g t h e t r i g l y c e r i d e and c h o l e s terol levels.

Chemical Formulas: Chemical Structures of Clofibrate (I), Treloxinate (11), and RU-25961 (III).

The two compounds JEI and I I I a r e much more p o t e n t ( i n R a t s ) t h a n t h e m a r k e t e d p r o d u c t I_. W h i l e i t i s easy t o r e c o g n i z e t h e common p - c h l o r o - p h e n o x y a c e t i c e s t e r i n a l l compounds, t h e o r i g i n o f t h e enhanced a c t i v i t i e s o f s t r u c t u r e s I_I and I I I i s q u e s t i o n a b l e and MIMETIC-GEMO w o u l d a p p e a r t o be u s e f u l f o r f i n d i n g o u t w h e t h e r t h e s e two m o l e c u l e s m i g h t n o t have more i m p o r t a n t f e a t u r e s i n common. Results H a v i n g s e p a r a t e l y c a l c u l a t e d t h e s t a b l e c o n f o r m e r s o f t h e two m o l e c u l e s (J3j), MIMETIC-GEMO c a l c u l a t i o n s w e r e t h e n p e r f o r m e d on t h e a c i d f o r m o f t h e compounds (7J, a l l o w i n g each one a t o l e r a n c e o f 15 k c a l / m o l e f o r i t s d e f o r m a t i o n s . A t t h e s t a r t i n g p o i n t t h e two p - c h l o r o - p h e n o x y g r o u p s w e r e c o i n c i d e n t and t h e more s t a b l e c o n f o r m e r was c h o s e n f o r each p r o d u c t . In this position the total s u r f a c e a r e a S j was e q u a l t o 369 A w h i l e t h e i s o l a t e d m o l e c u l e s had m o l e c u l a r e x p o s e d a r e a s o f 295 a n d 313 ft ^ t r e l o x i n a t e and RU-25961 r e s p e c t i v e l y . A f i r s t minimum was r e a c h e d when S j had d e c r e a s e d t o 341 with energies f o r the i s o l a t e d molecules (above t h e minimum t a k e n a s o r i g i n ) o f 14.6 k c a l / m o l e f o r 2

2

o

r

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

374

COMPUTER-ASSISTED DRUG DESIGN

t r e l o x i n a t e and 12.2 k c a l / m o l e f o r RU-25961. D u r i n g t h e m i n i m i z a t i o n t h e ^10IC2C^CI^) t o r s i o n a n g l e o f the f r e e phenyl group o f I I I has r o t a t e d f r o m an i n i t i a l v a l u e o f 58.0 d e g r e e s t o t h e f i n a l v a l u e o f 26.8 d e g r e e s , i n d i c a t i n g t h a t a m i m e t i s m i s p o s s i b l e , w h i c h i n c r e a s e s t o w a r d t h e l o w e s t v a l u e s o f $. S t a r t i n g f r o m t h e same p o i n t f o r JEI and a c o n f o r m a t i o n o f I I I o p t i m i z e d f o r $ = 0°, a s e c o n d minimum was o b t a i n e d w i t h t h e e n e r g y v a l u e s o f 9.7 k c a l / m o l e f o r t r e l o x i n a t e and 11.2 k c a l / m o l e f o r RU-25961. The f i n a l v a l u e s o f $ and S j b e i n g r e s p e c t i v e l y -7.2 d e g r e e s and 345 A . F i g u r e 1 shows t h e o v e r l a p o b t a i n e d i n t h i s c a s e . S p a c e f i l l i n g c o m p u t e r d r a w i n g s (8) f o r each m o l e c u l e a r e shown i n f i g u r e s 2a and 2b; t h e y show how a r e m a r k a b l e m i m e t i s m i s p o s s i b l e , w h i c h was n o t a t a l l o b v i o u s f r o m t h e s e p a r a t e 2-D c h e m i c a l s t r u c t u r e s o f t h e two compounds. U s i n g s e v e r a l o t h e r s t a r t i n g p o i n t s i t was n o t p o s s i b l e t o go b e l o w t h e v a l u e s o f 341 - 345 A o f t h e S j i n d e x a l r e a d y o b t a i n e d . I t a p p e a r e d p o s s i b l e t o i m p r o v e t h e s e r e s u l t s by i n c r e a s i n g t h e energy t o l e r a n c e p e r m i t t e d t o the m o l e c u l e s d u r i n g the o p t i m i z a t i o n F o r i n s t a n c e w i t h t o l e r a n c e v a l u e s o f 25 and 40 k c a l / m o l e t h e c o r r e s p o n d i n g minimum v a l u e s o f S j were r e s p e c t i v e l y 327 A ($=9°) and 318 A ($ = -10°). E l e c t r o n i c Aspect

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch018

2

2

2

2

We have f o u n d i t u s e f u l t o have i n f o r m a t i o n on b o t h m o l e c u l a r g e o m e t r y and e l e c t r o n i c c h a r a c t e r i s t i c s i n t h e same f r a m e . For t h i s p u r p o s e we have c o n c e i v e d a " f o u r - d i m e n s i o n a l s y m b o l i s m " (9) which c o n s i s t s o f a v i s u a l i z a t i o n of the envelope o f the molecules s t u d i e d , on t h e s u r f a c e o f w h i c h e n e r g y c o n t o u r s o f t h e e l e c t r o s t a t i c m o l e c u l a r p o t e n t i a l a r e drawn. T h i s k i n d o f r e p r e s e n t a t i o n i s shown i n f i g u r e s 3a and 3b. The m o l e c u l a r e n v e l o p e i s d e f i n e d by c o n s i d e r i n g t h a t each atom has a r a d i u s R s u c h as a

where Ry^ i s t h e Van d e r Waals r a d i u s o f t h e atom, and R a c o n s t a n t v a l u e t a k e n h e r e t o 1.5 A. The e l e c t r o s t a t i c m o l e c u l a r p o t e n t i a l used i n t h e s e c a l c u l a t i o n s i s t h e c l a s s i c a l C o u l o m b i c e x p r e s s i o n o f t h e i n t e r a c t i o n o f a + 1e c h a r g e a t t h e p o i n t c o n cerned. The e l e c t r o n i c d e n s i t i e s o f t h e atoms b e i n g o b t a i n e d by e x t e n d e d H u c k e l m o l e c u l a r o r b i t a l c a l c u l a t i o n s C l j y . From t h e s e d r a w i n g s i t can be s e e n t h a t t h e s i m i l a r i t i e s between t h e two molecules are not o n l y g e o m e t r i c a l but a l s o e l e c t r o n i c . The shape and t h e v a l u e s o f t h e e n e r g y c o n t o u r s a l l o w an a p p r e c i a t i o n o f t h e e x t e n t t o w h i c h t h e two compounds can be c o n s i d e r e d as m i m e t i c s . Conclusion 0

T h e s e d a t a show t h a t s i m i l a r i t i e s between c h e m i c a l compounds can e x i s t f r o m t h e p o i n t o f v i e w o f t h e m o l e c u l a r g e o m e t r y , w h i c h a r e n o t o b v i o u s f r o m t h e 2-D s t r u c t u r e s . What i s needed f o r t h e f u t u r e o f d r u g - d e s i g n i s t o d e v e l o p new o r i g i n a l m o l e c u l a r a r c h i t e c t u r e s c o n c e i v e d on t h e b a s i s o f s p a t i a l m i m e t i s m between g e o m e t r i c a l and e l e c t r o n i c f e a t u r e s .

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COHEN

Beyond

the 2-D Chemical

375

Structure

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch018

18.

Figure 1.

Overlap reached after minimization of S for the acid forms of treloxinate (II) and RU-25961 (III) (S = 345 A ) T

T

2

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch018

376

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COHEN

Beyond

the 2-D Chemical

Structure

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch018

18.

Figure 2b.

Three dimensional mimetism between the acid forms of RU-25961

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

377

378

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch018

COMPUTER-ASSISTED DRUG DESIGN

A 0 s 40.0

Figure 3a.

TETA =-220.0

LAHDA = 240.0

ALFA s 0.0

BETA =

ro t ).0

2 OAnnc s 0.0

Envelope of the acid forms of the molecules with the energy contours (Kcal) of the electrostatic molecular potential for treloxinate

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COHEN

Beyond

the 2-D Chemical

Structure

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch018

18.

Figure 3b.

Envelope of the acid forms of the molecules with the energy contours (Kcal) of the electrostatic molecular potential for RU-25961

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

379

380

COMPUTER-ASSISTED DRUG DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch018

Abstract QSAR theories are convenient for the design of new analogs of a known active compound but these theories are not always able to go beyond the chemical frame of the particular family studied. Considering structure-activity studies in the light of the three dimensional specificity of molecular interactions between drugs and receptors, conformational properties appear to be essential. To allow the design of new molecular architectures which could be able to mimic the essential features of known active compounds, i t is necessary to evaluate to what extent different molecules can mimic the spatial arrangement of atoms of a known active compound. The criterion of minimization of the total exposed molecular area of sets of overlapping molecules appears to be a powerful tool for revealing the 3-D mimetism between several molecules. During the minimization the molecules are not rigid but free to move and modify their geometries, provided that the molecular energies do not increase by more than a pre-established amount. Such calculations can reveal the biologically relevant molecular geometries and the possible associated pharmacophores. It is possible for the 3-D mimetism to be, not only geometrical but also electronic. Both properties can be visualized in a "four dimensional symbolism" which consists of a view of the envelope of the molecules studies, on the surface of which, energy contours of the electrostatic molecular potential are drawn. An example will be presented to illustrate the possibilities of this approach.

Literature Cited 1 COHEN N. C. Tetrahedron (1971) 27, 789 "GEMO, a computer program for the calculation of the preferred conformations of organic molecules." 2 Subroutine SCOOP supplied by the IBM Company. 3a CLEMENCE F., HUMBERT D. and DAGNAUX M. (1977) Belgian Patent BE 860,500. b CLEMENCE F., HUMBERT D., DAGNAUX M. and FOURNEX R. to be published. 4 GRISAR J. M., PARKER R. A., KARIYA T., BLOHM T. R., FLEMING R. W., PETROW V., WENSTRUP D. L. and JOHNSON R. G., J. Med Chem. (1972) 15, 1273 "Treloxinate and related hypolipidemic derivatives." 5 WITIAK D. T., NEWMAN H. A. I. and FELLER D. R. "Clofibrate and related Analogs. A Comprehensive Review." Marcel Dekker, New York, N.Y. 1977.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

18. COHEN

Beyond the 2-D Chemical Structure

381

6 Calculated with the GENO program (ref. 1). 7 It is admitted that the active principle is the free carboxylic acid form, and we refer in all the calculations to these forms. 8 COHEN N. C. "Computer program VIF" supplied on request.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch018

9 COHEN N. C. "Computer programs VISOPOT" unpublished work. 10 HOFFMANN R. J. Chem. Phys. (1963) 39, 1397 "An extended Hückel theory." RECEIVED

June 8, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

19 Conformational Analysis: A Module in a Program for the Design of Biologically Active Compounds A. J. STUPER, T. M. DYOTT, and G. S. ZANDER

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

Research Laboratory, Rohm and Haas Company, Spring House, PA 19477

The last decade has seen considerable progress made in understanding the relationship between chemical structure and biological activity. Despite this progress our ability to design active molecules is still quite unsophisticated. While we are certainly unable to a priori, design molecules possessing specific biological properties, we are able to identify several factors which govern this action. These are: 1) steric properties 2) transport properties 3) reactivity Certainly each factor does not operate independently of the others. Reactivity is influenced by the steric properties of a molecule, as is transport. Also these factors do not directly address the possible metabolic fate of a compound. However, such a division does allow us to concentrate on specific aspects of the problem and to direct our synthetic efforts accordingly. How then does this relate to the practical problem of developing new, effective, and safe drugs or other biologically active materials? There are certainly two ways to approach the problem. We can assume that by its nature the design problem i s i n t r a c t a b l e t o any t h e o r e t i c a l approach and t h e r e f o r e synthesize as many v a r i a n t s of a lead compound or t e s t as many new compounds as we can economically a f f o r d . For t h i s course o f a c t i o n , our success w i l l be a f u n c t i o n o f luck aided by i n t u i t i o n . On the other hand, we can take the approach that c o n t r o l o f those factors e f f e c t i n g a c t i v i t y w i l l i n c r e a s e the p r o b a b i l i t y o f reaching our goal. While the f a c t o r s i n f l u e n c i n g a c t i v i t y are not a l l under our c o n t r o l , an attempt t o c o n t r o l as many as p o s s i b l e w i l l r e duce the a r b i t r a r y nature inherent i n the f i r s t approach. Taking the l a t t e r approach there are two ways to guide our s y n t h e t i c e f f o r t s . To optimize the a c t i v i t y o f a compound we can attempt t o f i n d mathematical models which r e l a t e changes i n the above f a c t o r s t o changes i n the observed a c t i v i t y . We can then 0-8412-0521-3/79/47-112-383$08.00/0 ©

1979 A m e r i c a n C h e m i c a l Society

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

384

use these models t o a s s i s t us i n determining which analoges h o l d out the most promising chance f o r i n c r e a s e d a c t i v i t y . T h i s process i s w e l l documented, having been e x t e n s i v e l y developed by Hansch and co-workers (1,2). On the other hand, we may d e s i r e a compound which has the a c t i v i t y of a p a r t i c u l a r l e a d , but i s o f apparently d i f f e r e n t s t r u c t u r e . That i s a new l e a d . In t h i s case we would t r y t o design compounds which possess d i f f e r e n t chemical s t r u c t u r e s but maintain i d e n t i c a l s t e r i c , t r a n s p o r t , and r e a c t i v i t y p r o p e r t i e s . I t was f o r t h i s purpose that we have developed a computerized t o o l , c a l l e d MOLY, which can a s s i s t i n the molecular design problem. In t h i s paper we w i l l b r i e f l y review what t h i s system i s and d e t a i l our e f f o r t s t o parameterize the conformational a n a l y s i s s e c t i o n o f MOLY. Overview o f the MOLY Program We present t h i s s e c t i o n t o provide an understanding o f the context w i t h i n which the conformation a n a l y s i s program operates. MOLY i s an i n t e r a c t i v e system which employs computer graphics as the means o f communicating i t s r e s u l t s t o the s c i e n t i s t . The system has the f o l l o w i n g c h a r a c t e r i s t i c s : 1. 2. 3. 4. 5.

l a r g e |>1000K b y t e s ] modular command d r i v e n c o n s i d e r a b l e user prompting h i g h l y graphics o r i e n t e d

Figure 1 shows the system's a r c h i t e c t u r e . The main program, r e f e r r e d to as the d r i v e r , deciphers the user's d i r e c t i o n s and c a l l s the appropriate module. This module then i n t e r a c t s with the user to perform a s p e c i f i c task. There are seven major modules whose primary f u n c t i o n s a r e : 1. INPUT

- Input molecules by drawing them on the screen o f the graphics t e r m i n a l .

2. MODEL

- B u i l d a reasonable three dimensional model o f a molecule.

3.

- Perform a conformation

CONFOR

analysis.

4. ANALYZE - Prepare contour maps o f energy and p o p u l a t i o n as a f u n c t i o n o f r o t a t i o n about one o r two bonds. 5.

LOGP

- Estimate the value of the o c t a n o l / water p a r t i t i o n c o e f f i c i e n t .

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

19.

STUPER E T A L .

Conformational

Figure 1.

Analysis

Architecture of MOLY

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

385

COMPUTER-ASSISTED

386

6. FORMAT

DRUG DESIGN

- Provide an i n t e r f a c e between the i n t e r a c t i v e program and batch v e r s i o n s of quantum mechanical programs.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

7. COMPARE - Provide v i s u a l comparisons between d i f f e r e n t molecules by matching s e l e c t e d p o r t i o n s of t h e i r s t r u c t u r e s . In a d d i t i o n MOLY contains a l a r g e number of u t i l i t y programs which allow f o r e f f i c i e n t molecular s t o r a g e , r e t r i e v a l , o r i e n t a t i o n and d i s p l a y . The system i s w r i t t e n e n t i r e l y i n FORTRAN and executes on an IBM 370/158 under the MVS o p e r a t i n g system and the TSO t i m e - s h a r i n g system. User i n t e r a c t i o n i s v i a a T e k t r o n i x 4006 or 4010 graphics t e r m i n a l . Hard copy c a p a b i l i t i e s are prov i d e d v i a T e k t r o n i x photocopiers as w e l l as a Calcomp d i g i t a l plotter. The Conformation A n a l y s i s Module The e s s e n t i a l problem i n conformational a n a l y s i s i s t o f i n d the proper s p a t i a l o r i e n t a t i o n of a molecule's atoms. I f we cons i d e r the bond lengths and bond angles to be f i x e d then shape i s e n t i r e l y determined by the r o t a t i o n about s i n g l e bonds. The approximation of the f i x e d nature of bond lengths and angles i s w e l l accepted. These r e l a t i o n s are not s i g n i f i c a n t l y a l t e r e d by c r y s t a l or s o l v a t i o n f o r c e s . T o r s i o n a l i n t e r a c t i o n s which are of r e l a t i v e l y low energy are o f t e n d r a s t i c a l l y a l t e r e d by such f o r c e s . By c a l c u l a t i n g the molecular energy at a l l p o s s i b l e p o s i t i o n s of a l l r o t a t a b l e bonds, we are able to determine the r o t a t i o n angle at which the energy i s a minimum. The minimum energy conformations are those i n which the molecule i s most l i k e l y to be found i n the gas phase. I f these minima are s u f f i c i e n t l y deep, then i t i s l i k e l y that the same conformations w i l l be observed i n s o l u t i o n or the c r y s t a l l i n e s t a t e (3). The t o r s i o n a l angles i n the compounds which we s h a l l discuss w i l l be defined more p r e c i s e l y l a t e r . Here we s h a l l r e c a l l only that the t o r s i o n a l angle T about the Bond B-C i n the sequence of atoms A-B-C-D i s the angle through which the f a r bond C-D i s r o t a t e d r e l a t i v e to the near bond A-B. The c i s p l a n e r p o s i t i o n of bonds A-B and C-D represent a T = 0°.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

19.

STUPER E T A L .

Conformational

Analysis

387

T o r s i o n a l angles are considered p o s i t i v e f o r right-handed r o t a ­ t i o n ; when l o o k i n g along the bond B-C, the f a r bond C-D r o t a t e s clockwise r e l a t i v e to the near bond A-B. A l t e r n a t i v e l y , the p o s i t i v e angles are defined as 0° to 180°, measured f o r a c l o c k ­ wise r o t a t i o n , and negative angles as 0° t o -180°, measured f o r a counterclockwise r o t a t i o n . Since the valence of an atom i s g e n e r a l l y g r e a t e r than two the sequence of atoms A-B-C-D may be non-unique. However, i t i s s u f f i c i e n t to designate any four atoms which w i l l be used to d e f i n e the t o r s i o n a l angles used i n any p a r t i c u l a r problem. As e x p l a i n e d above, a Τ of 0° i s always the c i s p l a n e r arrangement of the atoms designated as d e f i n i n g the t o r s i o n a l angle. Conformational a n a l y s i s presents a c o m b i n a t o r i a l problem. An a n a l y s i s i n v o l v i n g 360 degree r o t a t i o n s i n D degree i n c r e ­ ments about Ν d i f f e r e n t bonds r e q u i r e s the examination of (360/D)^ conformations. The number of conformations i n c r e a s e s e x p o n e n t i a l l y with the number of bonds b e i n g r o t a t e d . For ex­ ample, i f D i s 30 degrees and Ν i s 2 then only 144 conformations must be examined, but i f Ν i s i n c r e a s e d to j u s t 5 the number of conformations jumps to 248,832. The sheer magnitude of such a problem r u l e s out even the f a s t e s t quantum mechanical technique. E m p i r i c a l methods are the only p r a c t i c a l means of examining such a l a r g e number of conformations. In our system, conformational a n a l y s i s i s performed by the module CONFOR. An a n a l y s i s i s defined by s p e c i f y i n g the bonds to' r o t a t e , the increment of r o t a t i o n , and the t o t a l number of degrees to r o t a t e . On the b a s i s of t h i s i n f o r m a t i o n the program c a l c u l a t e s the number of conformations which would r e s u l t . I f the problem i s too l a r g e to be done i n t e r a c t i v e l y (>5 CPU minutes), the problem can be s i m p l i f i e d or CONFOR can be used to i n i t i a t e a background batch job which w i l l perform the a n a l y s i s . In e i t h e r event once an a n a l y s i s i s complete the s c i e n t i s t can ask f o r the low energy conformations, look at energy contour maps, p l a c e the molecule i n v a r i o u s conformations f o r v i s u a l i n s p e c t i o n , etc. In CONFOR, conformation energy i s broken i n t o four terms. Ε where:

= E - + E -, + Ε,, ,+ Ε vdw coul hbond conj

conf E c

E

E

o

n

f

vdw

^

s

t

i s

n

e

r e l a t i v e energy of the conformation

t l i e

V

a

n

c

o

e r

W

a

^ interactions coul * * l ^ l S

t

i e

u

o

m

:

a

c

l

s

t e r m

>

accounting f o r s t e r i c

i n t e r a c t i o n term, accounting f o r

p a r t i a l charge i n t e r a c t i o n s hbond S bond term Ε . i s the conjugated bond term accounting f o r t o r s i o n a l preferences due t o conjugation E

i S

t

h

e

h

v

d

r

o

e

n

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

388

COMPUTER-ASSISTED DRUG DESIGN

The exact mathematical form of each energy term i s given i n Table I. j * * standard 6-12 Lennord-Jones p o t e n t i a l func­ tion. Ε ^ i s the c l a s s i c a l coulombic p o t e n t i a l f u n c t i o n . The dielectrîc constant of the s o l v e n t , ε, can be s p e c i f i e d by the s c i e n t i s t , otherwise i t d e f a u l t s to a value of 3 . 5 . Ehbond the hydrogen bond p o t e n t i a l f u n c t i o n developed by Scheraga et a l (4). T h i s f u n c t i o n has no angular dependence u n l i k e the func­ t i o n developed by Hopfinger et a l (5) which i n our experience i s overly r e s t r i c t i v e . The Ε . term was developed by us i n the course of t h i s work. I t i s an attempt to take i n t o account the t o r s i o n a l bar­ r i e r s caused by i n t e r a c t i o n of adjacent π systems and/or lone pairs. Such systems, e.g., amides, benzoic a c i d s , and dienes, show a preference f o r p l a n a r conformations which maximize con­ j u g a t i o n . The b a s i c form of the f u n c t i o n i s the standard cosine r e l a t i o n s h i p f r e q u e n t l y used f o r t o r s i o n a l energy: E

s

V

(

t

i e

w

U

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

i s

E

conj

where:

E

h

=

Bd-cos(N0)3

Β i s h a l f the b a r r i e r height Ν i s a symmetry constant, u s u a l l y 2 θ i s the t o r s i o n a l angle a

s

a

v

a

l

u

e

f

o

r

t

n

e

conj °f 0·0 p r e f e r r e d values of θ and i n ­ creases i n a smooth s i n u s o i d a l manner to a maximum of +2B as θ deviates from the p r e f e r r e d values. I f , however, e i t h e r or both of the systems i n conjugation are f u r t h e r conjugated, as i s f o r example a benzamide, where the carbonyl i s conjugated with both the amide n i t r o g e n and the phenyl r i n g , the e f f e c t i v e b a r r i e r i s decreased v i a two mechanisms : 1. The energy gained from conjugation i n i t i a l l y i s l e s s , i . e . , i n the case of the benzamide, s i n c e the carbonyl i s conjugated with the phenyl i t cannot conjugate as s t r o n g l y with the n i t r o g e n . 2. Energy l o s t by the r e d u c t i o n of conjugation due to r o t a t i o n about one bond can be p a r t i a l l y r e ­ covered by increased conjugation with the other conjugated groups. This e f f e c t , however, i s dynamic. For example, as the phenyl r i n g r o t a t e s out of conjugation w i t h the amide the t o r s i o n a l b a r r i e r about the amide bond returns to f u l l s t r e n g t h . Thus the e f f e c t i v e b a r r i e r to r o t a t i o n about a conjugating bond i s de­ pendent on: 1. 2. 3. 4.

11

the "normal b a r r i e r f o r such a bond any a d d i t i o n a l conjugated groups t h e i r conjugative s t r e n g t h t h e i r r e l a t i v e conformation

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

19.

STUPER E T A L .

Table 1.

Conformational

Mathematical Form of P o t e n t i a l Functions

Nonbonded

*v4,- V - U C

«:

where

Coulombic

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

A

] / d 6

r e p u l s i v e constant dependent on atoms i , j a t t r a c t i v e constant dependent on atoms i , j E u c l i d i a n distance between atoms i and j

coul

*1

d hbond

where

Ε r

Γ

Rotational Barriers

d 6

332.0 J

where

H-bond

389

Analysis

E

o

ΗΧ

tor

d d i e l e c t r i c constant p a r t i a l atomic charge on atom i E u c l i d i a n distance between atoms i and j E [ r / r ] 1 2 - 2.0E[r /r ]10 D

H X

o

H X

energy constant dependent on type of atoms p a r t i c i p a t i n g i n the hydrogen bond i n t e r n u c l e a r distance parameter dependent on type of atoms E u c l i d i a n distance between donor and acceptor atoms cos(N0 )] k

n

k 1 - Σ i*k

B.(l+cos(N0.)) —

— n

k

2-Σ

B

±

i=l where

B

B

e

9

n

k = the e f f e c t i v e b a r r i e r to r o t a t i o n about the bond of i n t e r e s t the non-conjugated b a r r i e r to r o t a t i o n about the bond of i n t e r e s t i - the non-conjugated b a r r i e r to r o t a t i o n about the i t h conjugated bond k = the t o r s i o n a l angle f o r the bond being rotated i - the t o r s i o n a l angle f o r the conjugate bonds k = number of bonds conjugated w i t h bond k Ν = a symmetry f a c t o r

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

390

COMPUTER-ASSISTED DRUG DESIGN

CONFOR a u t o m a t i c a l l y takes a l l of these f a c t o r s i n t o account. I t i n i t i a l l y f i n d s a l l conjugating bonds and assigns t h e i r "normal" b a r r i e r values and symmetry constants. These values are shown t o the s c i e n t i s t who can s p e c i f y a l t e r n a t i v e values. As the molecule i s b e i n g stepped through various conformations, the e f f e c t i v e t o r s i o n a l b a r r i e r s of any conjugating bonds are r e ­ c a l c u l a t e d and then used t o c a l c u l a t e Ε . v i a the formulas given i n Table I.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

P a r a m e t e r i z a t i o n of the Conformational A n a l y s i s Module Before we can use the r e s u l t s of conformational a n a l y s i s to p r e d i c t the s t e r i c c o n s t r a i n t s f o r a drug we must be reason­ ably c e r t a i n that the method i s p r o p e r l y parameterized. Our major concern i s that the minima i n d i c a t e d are l o c a t e d p r o p e r l y and the contour energy maps produced have a reasonable shape. T h i s requirement i s r a t h e r broad. Our experience has been that the accuracy of e m p i r i c a l f u n c t i o n s s u f f i c e f o r systems which show l i t t l e or no s t a b i l i z a t i o n due to resonance or other types of e l e c t r o n i c interchange. There are s e v e r a l ways to approach the p a r a m e t e r i z a t i o n problem. Previous groups have used comparisons to c r y s t a l pack­ i n g as a guage f o r the non-bonded i n t e r a c t i o n s ( 6 ) . They then f i n e tune the program u s i n g comparisons t o a l l valence MO c a l c u ­ l a t i o n s . We have chosen much the same route. Our f i n e t u n i n g was done by comparing our r e s u l t s t o those obtained using the PCILO technique of Pullman (7-9). We chose t h i s technique be­ cause of i t s accuracy and the a v a i l a b i l i t y of a l a r g e number of c a l c u l a t i o n s f o r v a r i o u s s m a l l molecules. In order to define the f a c t o r s i n v o l v e d i n p a r a m e t e r i z i n g the non-bonded p o t e n t i a l f u n c t i o n , i t i s necessary t o describe the f u n c t i o n a l approximations used. As have o t h e r s , we used the Lennord-Jones 6-12 p o t e n t i a l as the b a s i s f o r t h i s i n t e r a c t i o n . The form of t h i s i s : Ε

vw

= B/d

1 2

- A/d

6

(1)

E i s the energy of the i n t e r a c t i o n i n K c a l , d i s the d i s t a n c e , i n angstroms, between the i n t e r a c t i n g atoms, A and Β are con­ s t a n t s which depend on the type of atoms i n v o l v e d i n the i n t e r ­ a c t i o n . A t y p i c a l p o t e n t i a l i s shown i n F i g u r e 2. At l a r g e distances there i s e s s e n t i a l l y no c o n t r i b u t i o n to the conforma­ t i o n a l energy, but as the distance decreases t h i s energy becomes i n c r e a s i n g l y a t t r a c t i v e . With a f u r t h e r decrease i n distance the atoms get too c l o s e and q u i t e r a p i d l y s t a r t to r e p e l l each other. There are two f a c e t s to the Lennord-Jones p o t e n t i a l f u n c t i o n which i n t e r e s t us, the e q u i l i b r i u m distance d and the w e l l depth E . These parameters are r e l a t e d to A and Β by: w

Q

0

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

STUPER E T A L .

Conformational

Analysis

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

19.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

391

COMPUTER-ASSISTED DRUG DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

392

Figure 3.

Thirteen molecules used for comparison to PCILO

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

STUPER E T A L .

L.

Conformational

PSEUOQflMTLEINE

Analysis

M

PSEUDOLIOOCFIINE

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

394

COMPUTER-ASSISTED

A

(2)

Β

(3)

Our i n i t i a l s e t t i n g s f o r these constants were taken from the l i t e r a t u r e (10,11). U n l i k e the l i t e r a t u r e references we do not d i f f e r e n t i a t e ~ t n e atoms a c c o r d i n g t o h y b r i d i z a t i o n . The l i t e r ­ ature values thus served as an i n i t i a l approximation. In order to develop a c o n s i s t e n t set of constants we compared our c a l c u ­ l a t i o n s on the t h i r t e e n molecules i n F i g u r e 3 to those obtained by PCILO. We then adjusted our E and d values to o b t a i n r e ­ s u l t s which were c o n s i s t e n t with the PCILO c a l c u l a t i o n s . Table I I l i s t s the values of A, B, d , and Ε which r e s u l t e d from t h i s comparison. Note that i t was necessary to d i f f e r e n t i a t e between aromatic and non-aromatic hydrogens. This parameterization i s only a p p r o p r i a t e f o r H, C, 0, N, and S. The values f o r the other elements l i s t e d represent the i n i t i a l approximations. Our d values are a l l somewhat h i g h e r than those used by Hopfinger (10) and s m a l l e r than those used by Scheraga (11). The d i f f e r e n c e between our values and H o p f i n g e r s i s proEably due to our not d i v i d i n g the atoms a c c o r d i n g to valence. The Scheraga values are higjtier because the minimum energy d i s t a n c e s are based upon contact d i s t a n c e s somewhat l a r g e r than the Van der Waals contact distance. Q

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

DRUG DESIGN

Q

Q

1

We have reproduced s e v e r a l contour maps t o demonstrate the degree of comparison between PCILO and CONFOR. These p l o t s are shown i n F i g u r e s 4 t h r u 8. To generate these maps the molecules were p l a c e d i n the geometeries s p e c i f i e d by Pullman (7-9) and the bonds i n d i c a t e d i n F i g u r e 3 were r o t a t e d . The reference atoms f o r the t o r s i o n a l angles those used by Pullman. Partial atomic charges f o r use i n the Coulombic p o t e n t i a l f u n c t i o n were obtained from CNDO c a l c u l a t i o n s . The PCILO contour maps r e p r e ­ sent c a l c u l a t i o n s having a r e s o l u t i o n of 30 degrees about each bond. Our maps were generated u s i n g r o t a t i o n a l increments of 10 degrees. In general the agreement between the two methods was q u i t e c l o s e . Phenethylamine (Figure 3a) and Pseudoprocaine (Figure 3k) are t y p i c a l examples of c a l c u l a t i o n s which compare q u i t e c l o s e l y . Both the l o c a t i o n o f the minima and the o v e r a l l shape o f the map are very c l o s e to those obtained by PCILO. The map f o r Ephedrine (Figure 3b) has the same general shape; however, the s t a b i l i z a t i o n at T 2 - 60 degrees i s more pronounced than that shown by PCILO. A l s o , the minima f o r T i = ± 60, T = 0 are about 1 K c a l h i g h e r than that found by PCILO. I t i s not c l e a r why we see a l a r g e r s t a b i l i z a t i o n at Τχ = ± 60, T = 60. T h i s could be a r e s u l t of improper non-bonded terms. I t may a l s o be a f u n c t i o n of the d i f f e r e n c e i n the r e s o l u t i o n of the two maps. A s i m i l a r d i f f e r e n c e i s seen i n the map f o r Norephedrine (Figure 3d). Our c a l c u l a t i o n s show that at a T = ± 60, T = 60, there i s a r e g i o n of s t a b i l i t y . F i g u r e 9 shows three views of 2

2

x

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

2

19.

STUPER E T A L .

Table I I .

Conformational

395

Analysis

Values f o r the Nonbonded P o t e n t i a l Function

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

Hydrogen

A

Η 70.353

C 175.387

Ν 129.6811

Ρ 264.8311

0 123.7239

S 289.9912

Β

6281.149

33004.1

24024.57

78276.24

17088.45

95562.36

do

2.373

2.687

2.68

2.897

2.55

2.95

Eo

-0.197

-0.233

-0.175

-0.224

-0.225

-0.220

A

F 79.67815

Cl 272.4885

Br 299.1173

I 437.8515

AH 32.80541

Β

9336.187

80706.48

88410.22

166418.3

1217.415

do

2.783

2.898

2.897

3.021

2.05

Eo

-0.170

-0.230

-0.253

-0.288

-0.221

Carbon

A

H 175.387

C 522.0883

Ν 502.2265

Ρ 875.9980

0 446.1175

S 998.1056

Β

33004.1

240791.7

190507.2

616858.8

132680.5

680474.6

do

2.687

3.12

3.02

3.348

2.90

3.33

Eo

-0.233

-0.283

-0.331

-0.311

-0.375

-0.366

A

F 264.9297

Cl 906.5424

Br 1043.719

I 1475.163

AH 175.3848

Β

99698.52

636883.0

767148.0

1346600.

33004.10

do

3.016

3.346

3.372

3.496

2.687

Eo

-0.176

-0.323

-0.355

-0.404

-0.233

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG

396

Table I I .

Values f o r the Nonbonded P o t e n t i a l Function

DESIGN

(cont'd.)

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

Nitrogen

A

Η 129.6811

C 502.2265

Ν 337.3978

Ρ 741.0352

0 383.3762

S 934.8268

Β

24024.57

190507.2

130547.3

435819.9

128927.4

483352.4

do

2.68

3.02

3.03

3.250

2.96

3.18

Eo

-0.175

-0.331

-0.218

-0.315

-0.285

-0.452

A

F 224.7778

Cl 752.4295

Br 854.4915

I 1216.361

AH 129.6811

Β

56642.43

450756.5

529098.3

941178.8

24024.57

do

2.82

3.26

3.277

3.401

2.68

Eo

-0.223

-0.314

-0.345

-0.393

-0.175

Phosphorous

A

H 264.8311

C 875.9980

Ν 41.0352

Ρ 1474.461

0 725.8096

S 1562.526

Β

78276.24

616858.8

435819.9

1709147.

343864.0

1436368.

do

2.897

3.348

3.250

3.638

3.13

3.50

Eo

-0.225

-0.311

-0.315

-0.318

-0.383

-0.425

A

F 477.570

Cl 1032.84

Br 1420.615

I 1994.231

AH 264.8311

Β

331501.9

716969.2

1233586.

2138148.

78276.24

do

3.34

3.56

3.467

3.591

2.897

-0.172

-0.372

-0.409

-0.465

-0.224

E

o

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

19.

STUPER E T A L .

Table I I .

Conformational

Analysis

397

Values f o r the Nonbonded P o t e n t i a l Function (cont'd.)

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

Oxygen

A

Η 123.7239

C 446.1175

Ν 383.3762

Ρ 725.8096

0 347.0114

S 776.8652

Β

17088.45

132680.5

128927.4

343864.0

87258.63

331604.2

do

2.55

2.90

2.96

3.13

2.82

3.08

Eo

-0.225

-0.311

-0.285

-0.383

-0.345

-0.455

A

F 222.7845

Cl 743.9333

Br 873.6900

I 1244.813

AH 132.7183

Β

49239.03

368957.9

462066.7

825990.9

19571.27

do

2.76

3.16

3.192

3.315

2.58

Eo

-0.252

-0.375

-0.413

-0.469

-0.225

Sulfur H

C

Ν

Ρ

0

S

Α Ι 289.9912

998.1056

934.8268

1562.526

776.8652

1683.851

Β

95562.36

680474.6

483352.4

1436368.

331604.2

157683.0

d

0

2.95

3.33

3.18

3.50

3.08

3.5

E

0

-0.220

-0.366

-0.452

-0.452

-0.455

-0.458

F A I 474.7878

Cl 1609.260

Br 1561.998

I 2189.843

AH 289.9912

Β

231917.1

1610520.

1379998.

2383406.

95562.36

d

0

3.15

3.55

3.477

3.600

2.95

E

0

-0.243

-0.402

-0.442

-0.503

-0.220

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

398

COMPUTER-ASSISTED DRUG DESIGN

Table I I .

Values f o r the Nonbonded P o t e n t i a l Function

(cont'd.)

Florine

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

H

C

Ν

Ρ

0

S

79.67815

264.9297

224.7778

477.570

222.7845

474.7878

9336.187

99698.52

56642.43

331501.9

49239.03

231917.1

2.783

3.016

2.82

3.34

2.76

3.15

-0.170

-0.176

-0.223

-0.172

-0.252

-0.243

F

Cl

Br

I

AH

135.7213

456.2523

381.9460

544.8931

79.10228

37137.62

295690.5

187993.1

337396.0

9201.722

2.86

3.30

3.154

3.277

2.48

-0.124

-0.176

-0.194

-0.220

-0.170

Chlorine H

C

Ν

Ρ

0

S

272.4885

906.5424

752.4295

1032.84

743.9333

1609.260

80706.48

636883.

450756.5

716969.2

368957.9

1610520.

2.898

3.346

3.26

3.56

3.16

3.55

-0.230

-0.323

-0.314

-0.372

-0.375

-0.402

F

Cl

Br

I

AH

A I 456.2523

788.0722

1068.890

1503.2822

272.4885

Β

295690.5

510738.3

855184.3

1486748.

80706.48

d

Q

3.30

3.70

3.420

3.543

2.898

E

0

-0.176

-0.304

-0.334

-0.380

-0.230

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

19.

STUPER E T A L .

Table I I .

Conformational

Analysis

399

Values f o r the Nonbonded P o t e n t i a l F u n c t i o n (cont'd.)

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

Bromine

A

Η 299.1173

C 1043.719

Ν 854.4915

Ρ 1420.615

0 873.6900

S 1561.998

Β

88410.22

767148.0

529098.3

1233586.

462066.7

1379998.

do

2.897

3.372

3.277

3.467

3.192

3.477

Eo

-0.253

-0.355

-0.345

-0.409

-0.413

-0.442

A

F 381.9460

Cl 1068.890

Br 1388.129

I 1938.128

AH 299.1173

Β

187993.1

855184.3

1309037.

2246615.

88410.22

do

3.154

3.420

3.515

3.638

2.897

Eo

-0.194

-0.334

-0.368

-0.418

-0.253

Iodine

A

H 437.8515

C 1475.163

Ν 1216.361

Ρ 1994.231

0 1244.813

S 2189.843

Β

166418.3

1346600.

941178.8

2138148.

825990.9

2383406.

do

3.021

3.496

3.401

3.591

3.315

3.600

Eo

-0.288

-0.404

-0.393

-0.465

-0.469

-0.503

A

F 544.8931

Cl Br 1503.2822 1938.128

I 2693.000

AH 437.8515

Β

337396.0

1486748.

2246615.

3816973.

166418.3

do

3.277

3.543

3.638

3.762

3.021

Eo

-0.220

-0.380

-0.418

-0.475

-0.288

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

400

Table I I .

Values f o r the Nonbonded P o t e n t i a l Function

(cont'd.)

AH

A

Η 32.80541

C 175.3848

Ν 129.6811

Ρ 264.8311

0 132.7183

S 289.9912

Β

1217.415

33004.10

24024.57

78276.24

19571.27

95562.36

do

2.05

2.687

2.68

2.897

2.58

2.95

E

-0.221

-0.233

-0.175

-0.224

-0.225

-0.220

A

F 79.10228

Cl 272.4885

Br 299.1173

I 437.8515

AH 22.22401

Β

9201.722

80706.48

88410.22

166418.3

629.9831

do

2.48

2.898

2.897

3.021

1.96

Eo

-0.170

-0.230

-0.253

-0.288

-0.196

G

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

ez.ao

-]

a

I—»

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

ζ:

Ο

Ο

I

a

>

ι

8 Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Conformational

Analysis

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

STUPER E T A L .

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

Figure 9.

View of norephedrine showing the lack of any replusive interactions

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

19.

STUPER E T A L .

Conformational

Analysis

407

t h i s c o n f i g u r a t i o n . You w i l l note that there are no obviously r e p u l s i v e i n t e r a c t i o n s . I t appears that PCILO simply f i n d s the a l t e r n a t i v e s t a t e s to be more a t t r a c t i v e than does our method. The map f o r Sympath-1 (Figure 3g) appears to l o c a t e the minima p r o p e r l y , however, the shape i s somewhat d i f f e r e n t from that c a l c u l a t e d by PCILO. We show a l a r g e r r e p u l s i o n about the center of the map. This could be a f u n c t i o n of the r e s o l u t i o n used i n the PCILO c a l c u l a t i o n s , but more l i k e l y i n v o l v e s b a s i c d i f f e r e n c e s between the two methods. For our purposes t h i s map i s s u f f i c i e n t l y accurate.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

Comparisons f o r Other Compounds For the purpose of t e s t i n g the a p p l i c a b i l i t y of the CONFOR r o u t i n e to s t r u c t u r a l types other than those used i n the par­ a m e t e r i z a t i o n , we have performed many c a l c u l a t i o n s . We present three such comparisons below. A p a r t i c u l a r l y i n t e r e s t i n g set of c a l c u l a t i o n s are those we performed on the g l y c y l and v a l y l amino a c i d r e s i d u e s . Pullman has reported work on both molecules (12). In order to compare our r e s u l t s we reproduced these c a l c u l a t i o n s using the CONFOR module. Figure 10 shows a comparison of the maps f o r the g l y c y l residue. The dots on the maps represent known conformations of g l y c y l residues i n g l o b u l a r p r o t e i n s . In the case of the v a l y l residue PCILO p r e d i c t s a g l o b a l minimum where our method p r e d i c t s a maximum. As seen i n Figure 11 the conformation of the v a l y l residue i n g l o b u l a r p r o t e i n s occupies the minimum regions l o c a t e d by CONFOR and what would be a l o c a l minima i n the PCILO method. The b a r r i e r between Ψ = 270, Φ = 60 and ψ = 210, Φ = 300 shown by CONFOR i s due to the c l o s e approach of a hydrogen from the i s o p r o p y l and the oxygen of the carbonyl. The distance being only 1.81A. T h i s i s w e l l i n t o the r e p u l s i v e s t a t e of the Van der Waals i n t e r a c t i o n . Figure 12 shows one view of t h i s i n t e r a c t i o n . C l e a r l y f o r t h i s to be a minimum some s o r t of bonding must be o c c u r r i n g . Apparently PCILO i n d i c a t e s a weak hydrogen bond between t h i s hydrogen and the carbonyl oxygen. While there i s some evidence f o r the existence of C-H 0 hydrogen bonds, such bonds are experimentally observed only when the carbon a l s o bears at l e a s t one strong e l e c t r o n withdrawing group (13). I n i t i a l l y the i s o p r o p y l group was f i x e d i n the same conformation as that used by PCILO. I f we allow the i s o p r o p y l group to r e l a x i n order to remove the carbonyl-hydrogen i n t e r a c t i o n , we see a corresponding lowering of the b a r r i e r ; how­ ever, we are not able to obtain a l o c a l minimum i n t h i s r e g i o n . This leads us to question whether PCILO has i n d i c a t e d a r e a l i s t i c minima f o r t h i s r e s i d u e . The contour map f o r the r e l a x e d i s o ­ p r o p y l group i s shown i n Figure 13. I t i s i n t e r e s t i n g to note that the c a l c u l a t i o n f o r the r e l a x e d s t r u c t u r e r e q u i r e d the com­ p u t a t i o n of 186,624 separate conformations. Such a computation i s c e r t a i n l y i m p r a c t i c l e using the more time consuming semi-

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

408

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Figure 11.

Comparison of the energy contours calculated for the valyl residue (see Figure 4 for the meaning of the contour symbols)

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

COMPUTER-ASSISTED DRUG DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

410

Figure 12. View of the valyl residue showing the interaction between the carbonyl and one of the hydrogens on the isopropyl. This conformation is the minimum energy conformation as calculated by PCILO (Figure 11).

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

19.

STUPER E T A L .

Conformational

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

VR1 Τ Ι

Analysis

411

Π Τ P F P T Τ nF

ο ο

• ο

'-18D.00

-1U4.00

-108.00

-72.00

-36.00

RT0MÎ = 3

0.00

36.00

72.00

108.00

1W.0D

ΑΤ0Μ2= 4

CONTOUR VALUES ο + Χ

ζ

Υ

χ

1.00 2.00 3.00 4.00 5.00 6.00 θ.00 10.00 14.00 20.00

Figure 13. Contour map for the valyl residue calculated using CONFOR. This map was generated by allowing the isopropyl group to relax and seek a minimum energy conformation.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

180.00

COMPUTER-ASSISTED DRUG DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

412

Figure 14.

Energy vs. rotational angle plot for 7,8-benzflavone. The global minimum is located at 22°, the measured angle was 23°.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

19.

STUPER E T A L .

Conformational

Analysis

413

e m p i r i c a l methods. As a f i n a l example o f the u t i l i t y o f the program, we report a c a l c u l a t i o n on 7,8 benzflavone. The c r y s t a l s t r u c t u r e o f t h i s molecule has been reported by Glusker e t a l (14). F i g u r e 14 shows the map o f energy versus r o t a t i o n angle f o r the phenyl r i n g . The g l o b a l minimum was p r e d i c t e d t o be at 22 degrees. The a c t u a l value from the c r y s t a l s t r u c t u r e was 23 degrees.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

Conclusions The p a r a m e t e r i z a t i o n o f our conformational a n a l y s i s program appears t o give r e s u l t s which are l a r g e l y i n agreement with the semi-empirical quantum mechanical PCILO technique. The method i s capable o f producing data which i s reasonably accurate. This t o o l promises t o be o f great a i d i n s t u d y i n g the s t e r i c r e quirements o f a drug.

Literature Cited 1. C. Hansch, "A Quantitative Approach to Biochemical Structure-Activity Relationships," Acc. Chem. Res., 2, 232 (1969). 2. W. V. Valkenburg (Ed.), "Biological Correlations - The Hansch Approach," Advances in Chemistry Series, No. 114, American Chemical Society, Washington, D.C., 1972. 3. B. Pullman and P. Courriére, "Molecular Orbital Studies on the Conformation of Pharmacological and Medicinal Compounds," the Jerusalem Symposium on Quantum Chemistry and Biochemistry V, 547 (1973). 4. R. F. McGuire, F. A. Momany and H. A. Scheraga, "Energy Parameters in Polypeptides V an Empirical Hydrogen Bond Potential Function Based on Molecular Orbital Calculations," Jour. Phys. Chem., 76(3), 375 (1972). 5. H. J. R. Weintraub and A. J. Hopfinger, "Conformational Analysis of Some Phenethylamine Molecules," J. Theor. Biol., 41, 53 (1973). 6. F. A. Momany, L. M. Carruthers, R. F. McGuire, and H. A. Scheraga, "Energy Parameters in Polypeptides VII. Geometric Parameters, Partial Atomic Charges, Nonbonded Interactions, Hydrogen Bond Interactions, and Intrinsic Torsional Potentials for the Naturally Occurring Amino Acids," Jour. Phys. Chem., 79(22), 2361 (1975). 7. J. L. Coubeils and B. Pullman, "Quantum-Mechanical Study of the Conformational Properties of Drugs with Local Anesthetic Action," Mol. Pharm. 8, 278 (1972).

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

414

COMPUTER-ASSISTED DRUG DESIGN

8. J. L. Coubeils, P. Courriére and B. Pullman, "Quantum-Mechanical Study of the Conformational Properties of Sympatholytic Compounds," J. Med. Chem. 15(5), 453 (1972). 9. B. Pullman, J. L. Coubeils, P. Courrieré, and J. P. Gervois, "Quantum-Mechanical Study of the Conformational Properties of Phenethylamines of Biochemical and Medicinal Interest," Jour. Med. Chem. 15(1), 17 (1972).

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch019

10. A. J. Hopfinger, "Conformational Properties of Macromolecules," Academic Press, New York, 1973. 11. F. A. Momany, L. M. Carruthers, R. F. McGuire and H. A. Scherage, "Intermolecular Potentials from Crystal Data III. Determination of Empirical Potentials and Application to the Packing Configurations and Lattice Energies in Crystals of Hydrocarbons, Carboxylic Acids, Amines, and Amides," Jour. Phys. Chem., 78(16), 1595 (1974). 12. C. B. Anfinsen and John T. Edsall (Ed.), "Advances in Protein Chemistry," Academic Press, New York, pp. 348-562 (1974). 13. D. June Sutor, "Evidence for the Existence of C-H---O Hydrogen Bonds in Crystals." Jour. Chem. Soc., 1105 (1963). 14. Personal communication, Dr. J. P. Glusker. RECEIVED

June 8, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

20 New Optimal Strategies for Ab-initio Quantum Chemical Calculations on Large Drugs, Carcinogens, Teratogens, and Biomolecules JOYCE J. KAUFMAN, HERBERT Ε. ΡΟΡΚΙΕ, and P. C. HARIHARAN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch020

Department of Anesthesiology, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, and Department of Chemistry, The Johns Hopkins University, Baltimore, MD 21218 Our group has a long standing i n t e r e s t i n quantum chemical c a l c u l a t i o n s on l a r g e drug and biomolecules. The f i r s t a l l valence three-dimensional c a l c u l a t i o n s reported on any such mole­ c u l e s were extended Hiickel c a l c u l a t i o n s on p y r i d i n e aldoxime anta­ g o n i s t s t o organophosphorus i n t o x i c a n t s we presented at the I l l r d I n t e r n a t i o n a l Pharmacological Congress, Sao Paulo, B r a z i l , J u l y I966 ( l _ , 2) . These c a l c u l a t i o n s were c a r r i e d out w i t h a program we wrote o u r s e l v e s i n I963 from the o r i g i n a l papers o f Wolfsberg and Helmholz, 1952 (3.) , and Eberhardt, Crawford and Lipscomb, I956 (h) , t h e same papers from which the extended Hiickel method of Hoffman (5) was d e r i v e d and which he named "extended Hiickel". We even wrote i n I965-I966 an i t e r a t i v e scheme f o r charge c o n s i s ­ tency i n the extended Hiickel method. I n s p i t e o f our e a r l y compu­ t a t i o n a l c a p a b i l i t y our study on the p y r i d i n e aldoxime antagonists was the one and o n l y time we ever used the extended Hiickel method f o r c a l c u l a t i o n s on drugs, biomolecules or any b i o l o g i c a l , m e d i c a l or pharmacological problem. The reason that we never used t h e extended Hiickel method a g a i n f o r drug and b i o l o g i c a l systems was that we were aware o f the d e f i c i e n c i e s o f the method. I t d i d not (and s t i l l t o t h i s day does not) always g i v e a c a l c u l a t e d energy minimum even f o r s t r e t c h i n g a bond and since the method does not i n c l u d e e l e c t r o n - e l e c t r o n r e p u l s i o n i t cannot d i s t i n g u i s h between s i n g l e t and t r i p l e t s t a t e s (or doublet and quartet s t a t e s , e t c . ) . I t i s i n c r e d i b l e t h a t i n t h i s day and age extended Hiickel c a l c u l a ­ t i o n s ( i t e r a t i v e or not) a r e s t i l l being c a r r i e d out on drugs, biomolecules or carcinogens. I t i s a method whose time i s long since past. Instead, i n I963 we were already beginning t o c a r r y out abi n i t i o LCA0-M0-SCF c a l c u l a t i o n s on s i z a b l e rocket f u e l molecules, such as B2Hg with 56 Gaussian b a s i s f u n c t i o n s (6), using an e a r l y v e r s i o n of the P0LYAT0M program supplied t o us by the l a t e P r o f e s ­ sor John C. S l a t e r , which we converted f o r use on an IBM 709^. A f t e r u s i n g that POLYATOM program f o r o n l y a few s i z a b l e molecules i t became obvious f o r l a r g e r systems i t would be advantageous t o w r i t e a newer more e f f i c i e n t Gaussian i n t e g r a l program. We wrote 0-8412-0521-3/79/47-112-415$05.25/0 © 1979 A m e r i c a n C h e m i c a l Society

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch020

416

COMPUTER-ASSISTED

DRUG DESIGN

the MOSES program (Molecular O r b i t a l s ) (£) p a r t l y so named because Moses was a prophet and such a program could p r e d i c t molecular p r o p e r t i e s . The MOSES program was e f f i c i e n t and went through sev­ e r a l v e r s i o n s up through c o n t r a c t e d d o r b i t a l s by 19&J. I t imple­ mented perhaps among t h e most e f f i c i e n t algorithms f o r c a l c u l a t i n g i n t e g r a l s over c o n t r a c t e d Gaussian b a s i s f u n c t i o n s and symmetry adapted c o n t r a c t e d b a s i s f u n c t i o n s a t that time and probably even today. When Clementi was w r i t i n g h i s f i r s t IBMOL program he asked us t o check t h e accuracy o f h i s i n t e g r a l s program against those we c a l c u l a t e d u s i n g our MOSES program. Subsequently t h e i n t e g r a l s s e c t i o n of t h e MOSES program was g i v e n t o H. Basch when he was a p o s t d o c t o r a l a t B e l l Labs and he incorporated i t i n t o a l a t e r v e r ­ s i o n of t h e POLY ATOM program. Meanwhile, i n 196** we began u s i n g a CDC 6U00 computer and i n I965 a CDC 6600 computer with an o l d CHIPPEWA c o m p i l e r — b e f o r e a Scope compiler was even a v a i l a b l e . The MOSES program was converted immediately t o r u n on t h e CDC 6400 and CDC 6600 as soon as we got access t o them, and from t h a t day t o t h i s we remain devoted fans and great exponents o f t h e CDC 66ΟΟ s e r i e s and now o f t h e CDC 7000 serues and t h e CYBER s. We have always endeavored t o make optimal use o f t h e i r 60 b i t word l e n g t h . The MOSES program c o u l d handle 175 b a s i s f u n c t i o n s i n a CDC 6600 computer. However, CDC .6000 computer time was a v e r y l i m i t e d commodity t o us i n those y e a r s and we were i n t e r e s t e d s t i l l i n c a r r y i n g out quantum chemical c a l c u l a t i o n s on l a r g e mole­ cules. 1

Thus i n 196^ we d e r i v e d semi-rigorous LCA0-M0-SCF methods f o r three-dimensional molecular c a l c u l a t i o n s i n c l u d i n g e l e c t r o n - e l e c ­ t r o n r e p u l s i o n (8). T h i s paper was presented a t t h e January I965 S a n i b e l I n t e r n a t i o n a l Symposium on Atomic, Molecular and S o l i d S t a t e Theory where Pople presented h i s CNDO method and our paper appears back t o back i n t h e same Symposium i s s u e o f t h e J o u r n a l o f Chemical P h y s i c s i n which P o p l e s f i r s t papers on CNDO and NDDO appeared (£, 10) . There were four degrees o f neglect o f i n t e g r a l s i n our paper. The f i r s t and simplest resembled CND0» t h e next INDO, t h e t h i r d NDDO and t h e r e was y e t another l e s s approximate scheme. We programmed up t h e method and t r i e d i t on a few com­ pounds. We were s t i l l convinced that a b - i n i t i o computations were the o n l y r e a l l y a p p r o p r i a t e method f o r quantum chemical c a l c u l a ­ t i o n s on drugs and b i o l o g i c a l molecules. Having always o n l y a very small group we decided t o devote our major e f f o r t s t o abi n i t i o quantum chemical c a l c u l a t i o n s on l a r g e drug and biomolec u l e s and e s p e c i a l l y t o d e r i v i n g and implementing new and b e t t e r s t r a t e g i e s f o r a b - i n i t i o c a l c u l a t i o n s on such molecules. In t h e i n t e r v e n i n g years f o r computational t r a c t a b i l i t y we c a r r i e d out some c a l c u l a t i o n s w i t h l e s s r i g o r o u s quantum chemical techniques [CNDO (11)» INDO (11)» PCILO (12)] as w e l l as t o p o l o g ­ i c a l * and t o p o g r a p h i c a l f analyses on a v a r i e t y o f l a r g e drugs t o understand and p r e d i c t t h e i r c o n f o r m a t i o n a l p r o f i l e s , e l e c t r o n i c s t r u c t u r e s and p r o p e r t i e s and t h e mechanism o f a c t i o n of t h e i r biological effects. [^Topological s i m i l a r i t y — i n d i c a t e s t h a t i n 1

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch020

20.

KAUFMAN E T AL.

Ab-initio

Quantum

Chemical

Calculations

417

d i f f e r e n t molecules the same kind o f atoms a r e connected i n e x a c t l y t h e same way. Oftentimes a common t o p o l o g i c a l p a t t e r n o f atoms i s buried w i t h i n a s e r i e s of much l a r g e r molecules. fTopog r a p h i c a l s i m i l a r i t y , — i n d i c a t e s that i n d i f f e r e n t molecules two p o r t i o n s of t h e molecule bear t h e same s p a t i a l r e l a t i o n s h i p t o one a n o t h e r — a l t h o u g h not n e c e s s a r i l y t o p o l o g i c a l l y r e l a t e d . ] These included LCA0-M0-SCF c a l c u l a t i o n s on n e u r o l e p t i c s Cthe major t r a n q u i l i z e r s ) (13-20), n a r c o t i c s and n a r c o t i c a n t a g o n i s t s (13» 16, 18-23)· We were able t o i d e n t i f y t h e topographical and e l e c t r o n i c r e q u i s i t e s f o r n e u r o l e p t i c a c t i o n and we c a r r i e d out quantum chemi c a l c a l c u l a t i o n s on a h y p o t h e t i c a l s e r i e s of new e f f e c t i v e neurol e p t i c s ( l U , 15» 16, 179 18). Two years a f t e r our o r i g i n a l p r e s e n t a t i o n , s i x such compounds were reported as synthesized and animal t e s t e d and they were a l l e f f e c t i v e n e u r o l e p t i c s (2U). We c a r r i e d out t h e f i r s t a l l - v a l e n c e e l e c t r o n c a l c u l a t i o n s on narcot i c s , CNDO/2 c a l c u l a t i o n s on morphine, which were presented a t the S a n i b e l I n t e r n a t i o n a l Symposium on Atomic, Molecular and S o l i d S t a t e Theory January 1972 and appeared i n that Symposium i s s u e o f the I n t . J . Quantum Chem. (13) and we followed t h a t s h o r t l y with CNDO/2, INDO and PCILO c a l c u l a t i o n s on a v a r i e t y o f n a r c o t i c s and n a r c o t i c a n t a g o n i s t s presented at t h e S a n i b e l I n t e r n a t i o n a l Symposium January 197^ and published i n that Symposium i s s u e of t h e I n t . J . Quantum Chem. (21). In connection with these e a r l i e r quantum chemical studies we had a l s o extended t h e d e r i v a t i o n s o f some of t h e semi-rigorous techniques [such as d e r i v i n g t h e necessary expressions f o r i n c l u ding d o r b i t a l s i n t h e INDO method (25)],suggested procedures t o improve other methods [how t o improve t h e d e s c r i p t i o n o f l o n e p a i r s i n t h e PCILO method (26)1 and performed c a l c u l a t i o n s by v a r ious techniques comparing t h e r e s u l t s o f l e s s r i g o r o u s c a l c u l a t i o n s with our l a r g e b a s i s set a b - i n i t i o c a l c u l a t i o n s (27 >28). We thus have an e x c e l l e n t grasp o f t h e l i m i t s o f v a l i d i t y of l e s s than a b - i n i t i o quantum chemical c a l c u l a t i o n s compared t o a b - i n i t i o c a l c u l a t i o n s and compared t o experiment. We a l s o c a r r i e d out a few completely a b - i n i t i o c a l c u l a t i o n s on t h e n e u r o l e p t i c chloropromazine and on promazine (29) and on the n a r c o t i c morphone and t h e n a r c o t i c agonist-antagonist nalorphine (30) using IBMOL 6 (31) · However, even though IBMOL 6 had been w r i t t e n e s p e c i a l l y t o c a r r y out a b - i n i t i o c a l c u l a t i o n s on l a r g e molecules, and we had improved i t s use by such techniques as repacking t h e i n t e g r a l tapes so that f o r t h e f i r s t s i x i t e r a t i o n s we read only i n t e g r a l s 10""^ a.u. or l a r g e r , f o r t h e next s i x i t e r a t i o n s a l l i n t e g r a l s 5 X 10~6 a.u. or l a r g e r , and f o r t h e f i n a l few i t e r a t i o n s a l l i n t e g r a l s 10~7 a.u. or l a r g e r , t h e c a l c u l a t i o n s mentioned above that we d i d with IBMOL 6 convinced us that we were going t o have t o develop something s t i l l b e t t e r t o make computat i o n a l l y t r a c t a b l e r o u t i n e a b - i n i t i o c a l c u l a t i o n s on l a r g e drug and biomolecules. Ab-initio

MODPOT/VRDDO/MERGE

Technique

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch020

418

COMPUTER-ASSISTED DRUG DESIGN

I t was i n 197*+ t h a t we began development o f our new s e r i e s o f Gaussian i n t e g r a l programs e s p e c i a l l y designed f o r l a r g e mole­ c u l e s : MOLASYS (Molecular O r b i t a l C a l c u l a t i o n s on Large Systems) (.32, 33) and GIPSY [Gaussian I n t e g r a l Program System) (3^, 35) . MOLASYS and GIPSY c a l c u l a t e s,p,d and f i n t e g r a l s i n b l o c k s , t a k i n g f u l l advantage of t h e information common t o members o f t h e same block. We a l s o use the f u l l 60 b i t CDC word t o store small two e l e c t r o n i n t e g r a l s indexing t h e i n t e g r a l a l s o i n the same word u s i n g t h e l e a s t s i g n i f i c a n t b i t s f o r indexing and converting t h e i n t e g r a l t o f l o a t i n g p o i n t when i t i s used. We have compared t h e timings d i r e c t l y with those o f other general s,p, and d i n t e g r a l packages i n current usage (and which we o u r s e l v e s had used p r e ­ v i o u s l y ) . Our new i n t e g r a l program, GIPSY, f o r s,p and d i n t e g r a l s i s o f t h e order o f four times f a s t e r than R a f f e n e t t i ' s BIGGMOLI (36, 37) program and twice as f a s t as BIGGMOLI f o r s and ρ i n t e ­ g r a l s only. Our GIPSY program i s o f t h e order o f eight times f a s t e r f o r s,p and d i n t e g r a l s than POLYATOM Ç38) [improved CDC 6600 v e r s i o n (39)] and four times f a s t e r than POLYATOM (3£) f o r s and ρ i n t e g r a l s only. I n d i r e c t timing comparisons {ho) i n d i c a t e that our GIPSY program i s twice as f a s t as GAUSSIAN 70 (kl) f o r general s and ρ i n t e g r a l s with d i f f e r e n t exponents and of t h e same speed as GAUSSIAN 70 when t h e same exponents a r e used i n GAUSSIAN 70 f o r s and ρ f u n c t i o n s . The same algorithm i s used i n GAUSSIAN 76 jh2) . Recently there has been introduced a new method e s p e c i ­ a l l y e f f i c i e n t f o r e v a l u a t i o n of Gaussian i n t e g r a l s f o r b a s i s f u n c t i o n s of higher angular momentum (J+3) and t h e authors i n c o r ­ porated i t i n t o a new program c a l l e d HONDO (j+3.) · I n d i r e c t timing comparisons f o r s,p and d i n t e g r a l s reported (k3) f o r HONDO com­ pared t o PHANTOM (hh) (a QCPE CDC 6600 v e r s i o n of POLYATOM) and t o BIGGMOLI (36, 37.) i n d i c a t e that our GIPSY s,p and d i n t e g r a l p r o ­ gram i s probably a f a c t o r o f 1.3 f a s t e r than HONDO- An algorithm f o r d o r b i t a l s s i m i l a r t o that of HONDO i s used i n the newer v e r ­ s i o n of GAUSSIAN 76 (h2). We p l a n t o check t h e timing comparison f o r f o r b i t a l s between GIPSY and HONDO as soon as f e a s i b l e . But even more importantly, our programs incorporate s e v e r a l v e r y d e s i r a b l e f e a t u r e s as time-saving options t o our a b - i n i t i o computer programs: a charge conserving i n t e g r a l prescreening approximation (VRDDO) e s p e c i a l l y e f f e c t i v e f o r s p a t i a l l y extended molecules; a b - i n i t i o e f f e c t i v e core, model p o t e n t i a l s (M0DP0T) which enable one t o t r e a t only the valence e l e c t r o n s e x p l i c i t l y yet a c c u r a t e l y ; and a MERGE technique which enables us t o r e t a i n a l l the i n t e g r a l s f o r a s k e l e t a l fragment which remains unchanged and j u s t r e c a l c u l a t e t h e new i n t e g r a l s f o r added atoms or t h e i r geometry variâtions,both f o r i n t r a - and i n t e r m o l e c u l a r c a l c u l a t i o n s . Our VRDDO approximation ( v a r i a b l e r e t e n t i o n o f diatomic d i f f e r e n t i a l overlap) was i n s p i r e d i n part by a suggestion from s o l i d s t a t e p h y s i c s by W i l h i t e and Euwema {k5) . The approximation cons i s t s o f n e g l e c t i n g a l l o n e - e l e c t r o n i n t e g r a l s (both energy and overlap) and two-electron i n t e g r a l s that i n v o l v e b a s i s f u n c t i o n p a i r s φ.(1)φ.(ΐ) whose pseudo-overlap:

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

20.

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KAUFMAN

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cally

somewhat

o u r VRDDO p r o c e d u r e

VRDDO a p p r o x i m a t i o n has

MOLASYS (3£,

The

equal to

ρ s e u d o - o v e r l a p S*j

differs

however The

sion

contracted the

419

Calculations

f u n c t i o n whose e x p o n e n t calculating

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch020

Ab-initio

ET AL.

i>J

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

row

420

COMPUTER-ASSISTED DRUG DESIGN

hCi) = - |& - Z l / r k k -Γ Cz -N )(l

(2)

h

1

n

C/

k

c

+

A

l k

J^ik

e

2

k a

A

A

+

A

r

- 2k ik 2k

e

)

/

2

r

w

i k

η

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch020

+

? k

{ B

lsl

l s

k

> < l s

kl

+ B

2

2 s

l V
, |2s^> and |2p > a r e inner s h e l l atomic o r b i t a l s for t h e k-th core. B o n i f a c i c and Huzinaga (58, 59) have introduced Gaussian terms i n t o t h e one-electron p a r t o f t h e Hamiltonian t o account f o r the screening o f t h e n u c l e i by t h e core e l e c t r o n s and pseudopotent i a l terms t o prevent t h e buildup o f t h e valence molecular o r b i ­ t a l s i n t h e core r e g i o n s . B o n i f a c i c and Huzinaga d e r i v e d model p o t e n t i a l expressions f o r inner s,p and d o r b i t a l s . We extended the d e r i v a t i o n a l s o t o inner f o r b i t a l s . T h i s MODPOT procedure of B o n i f a c i c and Huzinaga has been introduced as an o p t i o n i n t o our MOLASYS and GIPSY computer programs. With t h e GIPSY computer program we can c a l c u l a t e t h e u s u a l o n e - e l e c t r o n o v e r l a p , k i n e t i c energy, nuclear a t t r a c t i o n and two-electron r e p u l s i o n i n t e g r a l s between s-, ρ-, d- and f - c o n t r a c t e d Gaussian f u n c t i o n s . I n a d d i ­ t i o n , t h e new type o f one-electron i n t e g r a l s r e s u l t i n g from t h e use o f t h e Bonifacic-Huzinaga Hamiltonian with s-, ρ-, d- and f type core atomic o r b i t a l s can be c a l c u l a t e d . We v e r i f i e d t h e accuracy o f t h e MODPOT method f o r a v a r i e t y of molecules by c a r r y i n g out t h e r e f e r e n c e c a l c u l a t i o n s with twoe l e c t r o n i n t e g r a l s accurate t o 6 decimal p l a c e s . Then t h e MODPOT c a l c u l a t i o n s were c a r r i e d out with t h e valence s h e l l two-electron i n t e g r a l s accurate t o 6 decimal p l a c e s and t h e MODPOT m o d i f i e d one-electron i n t e g r a l s . The same r e f e r e n c e atomic b a s i s set was used f o r both c a l c u l a t i o n s . Comparison o f t h e MODPOT r e s u l t s t o the completely a b - i n i t i o ones ( i n c l u d i n g inner s h e l l e l e c t r o n s ) showed t h a t t h e valence o r b i t a l energies and gross atomic popula­ t i o n s a r e a c c u r a t e * [see footnote page Ul9] t o more than 2 decimal p l a c e s (the average error i s 0.005 a.u.). The maximum e r r o r i n c

k

k

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch020

20.

KAUFMAN E T AL.

Ab-initio

Quantum

Chemical

Calculations

421

the o r b i t a l energies f o r t h e l a r g e s t molecule studied t o date i s o n l y 0.11 a.u. and i n t h e gross atomic p o p u l a t i o n s i s o n l y 0.010 a.u. I t should be emphasized that t h e accuracy obtained with t h e MODPOT approximation i s more than acceptable i f one wants t o reproduce a b - i n i t i o r e s u l t s f o r l a r g e molecules. Moreover, f o r molecules composed even o f two second row atoms, such as 01^» "the savings i n time between t h e MODPOT method compared t o t h e comp l e t e l y a b - i n i t i o i s a f a c t o r o f t e n . The savings i n time a l s o i n c r e a s e d r a m a t i c a l l y as t h e s i z e o f t h e molecule goes up. I f both t h e MODPOT and VRDDO approximations are introduced, t h e accuracy* [*see footnote page Ul9] with respect t o t h e r e f e r ence c a l c u l a t i o n s i s about t h e same as t h a t obtained u s i n g o n l y the MODPOT approximation. The maximum e r r o r i n t h e o r b i t a l energ i e s i s 0.012 a.u., i n t h e gross atomic p o p u l a t i o n s i s 0.009» i n the t o t a l o v e r l a p populations i s 0.027 and i n t h e d i p o l e moment

i s 0.009 a.u.

Since one u s u a l l y i s i n t e r e s t e d i n energy d i f f e r e n c e s r a t h e r than t h e t o t a l energy of a s i n g l e system, i t i s u s e f u l t o compare isomer energy d i f f e r e n c e s computed with t h e v a r i o u s procedures. In t h e 6-3G r e f e r e n c e c a l c u l a t i o n s (I18-U9) imidazole i s more s t a b l e than p y r a z o l e by 0.0150 a.u., p y r i m i d i n e i s more s t a b l e than p y r i d a z i n e by O.02U7 a.u., and p y r a z i n e i s more s t a b l e than p y r i d a z i n e by 0.0222 a.u. With t h e VRDDO method t h e corresponding energy d i f f e r e n c e s are 0.0153, 0.0258 and 0.0219 a.u. r e s p e c t i v e l y . Use of t h e MODPOT method y i e l d s v a l u e s o f 0.0136, 0.0219 and O.OI89 r e s p e c t i v e l y . F i n a l l y , t h e M0DP0T/VRDD0 method g i v e s v a l u e s o f 0.0139, 0.0231 and 0.0188 a.u. r e s p e c t i v e l y . Thus, even f o r t h e M0DP0T/VRDD0 method, t h e agreement with a b - i n i t i o r e s u l t s i s e x c e l l e n t ; 0.0011 a.u. f o r i m i d a z o l e - p y r a z o l e , 0.0016 a.u. f o r p y r i m i d i n e - p y r i d a z i n e and 0.003^ a.u. f o r p y r a z i n e - p y r i d a z i n e . The r e l a t i v e accuracy of t h e MODPOT/VRDDO method along a p o t e n t i a l energy surface (such as f o r molecular conformational changes or i n t e r a c t i o n s between two s p e c i e s , 0.0001 - 0.0002 a.u.) i s even greater than i t s absolute accuracy. For one aromatic r i n g with one s u b s t i t u e n t (such as NO2) t h e VRDDO c a l c u l a t i o n i s 1.5 times f a s t e r than t h e r e f e r e n c e c a l c u l a t i o n (using our own f a s t a b - i n i t i o programs [32, 33, 3^» 35]> t h e MODPOT c a l c u l a t i o n i s t h r e e times f a s t e r and t h e M0DP0T/VRDD0 c a l c u l a t i o n i s f i v e times f a s t e r ) . Moreover, t h e r e l a t i v e i n c r e a s e i n speed goes up even more d r a m a t i c a l l y as t h e molecules get l a r g e r . We v e r i f i e d t h e accuracy o f t h e MODPOT method f o r a v a r i e t y of molecules (V7, k8, U9) by c a r r y i n g out t h e r e f e r e n c e c a l c u l a t i o n s with two-electron i n t e g r a l s accurate t o 6 decimal p l a c e s . Then t h e MODPOT c a l c u l a t i o n s were c a r r i e d out with t h e valence s h e l l two-electron i n t e g r a l s accurate t o 6 decimal p l a c e s and t h e MODPOT m o d i f i e d one-electron i n t e g r a l s . The same r e f e r e n c e atomic b a s i s set was used f o r both c a l c u l a t i o n s . Comparison o f MODPOT r e s u l t s t o t h e completely a b - i n i t i o ones ( i n c l u d i n g inner s h e l l e l e c t r o n s ) showed t h a t t h e valence o r b i t a l energies and gross

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

422

COMPUTER-ASSISTED DRUG

DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch020

atomic p o p u l a t i o n s are accurate t o more than 2 decimal p l a c e s ( t h e average e r r o r i s 0.005 a.u.). Moreover, t h e accuracy o f t h e MODPOT r e s u l t s compared t o a b - i n i t i o i s much greater (0.005 eV [50]) f o r c a l c u l a t i n g e x c i t a t i o n energies, e l e c t r o n a f f i n i t i e s , t o t a l energy d i f f e r e n c e s between isomers, p o t e n t i a l energy curves, e t c . , s i n c e these i n v o l v e o n l y energy d i f f e r e n c e s . Moreover, f o r molecules composed even o f two second row atoms, such as C ^ » "the savings i n time between t h e MODPOT method compared t o t h e com­ p l e t e l y a b - i n i t i o i s a f a c t o r o f t e n . The savings i n time a l s o i n c r e a s e s d r a m a t i c a l l y as t h e s i z e o f t h e molecule goes up. As a t e s t o f t h e e f f i c i e n c y o f t h e method, we r a n a b - i n i t i o M0DP0T/VRDD0 c a l c u l a t i o n s on t h e DNA bases ($k) : Molecule

No. Atoms

C,N,0 DNA C o n s t i t u e n t s

No. B a s i s Fns.

Time (minut es) Integrals*

H

Cytosine

8

5

37

Guanine

11

5

k

Thymine

9

6

38

Adenine

10

5

9

5.1 11.2

SCFt

2.0 k.3

ΊΛ

3.1

9.2

3-5

*CDC 6600 computer, FTN, 0PT=0. (The i n t e g r a l s run even ~75# f a s t e r under 0PT=2 on a CDC 6600 computer which supports a f u l l 0PT=2 compiler.) fCDC 6600 computer, FTN, 0PT=2. We have obtained t h e MODPOT parameters f o r t h e f o r m u l a t i o n we use by matching MODPOT c a l c u l a t i o n s t o t h e completely a b - i n i t i o c a l c u l a t i o n s f o r atoms or small molecules u s i n g t h e same atomic r e f e r e n c e b a s i s set. We a r e c u r r e n t l y working on matching these parameters f o r higher elements. There are a number o f methods f o r t r e a t i n g t h e e f f e c t i v e core p o t e n t i a l s , r e l a t i v i s t i c e f f e c t i v e core p o t e n t i a l s (and some comparisons and c r i t i q u e s ) . Space l i m i t a t i o n does not permit us t o l i s t a l l these r e f e r e n c e s . F o r a complete up-to-date b i b l i o g r a p h y on v a r i o u s model p o t e n t i a l methods see our recent NATO Advanced Study I n s t i t u t e l e c t u r e (6θ). However, i t appears t h a t t h e core p r o j e c t i o n model p o t e n t i a l s o f the B o n i f a c i c and Huzinaga type we use which y i e l d valence o r b i ­ t a l s with t h e u s u a l o s c i l l a t o r y behavior i n t h e core r e g i o n may have advantages f o r c a l c u l a t i o n o f c o r r e l a t i o n energies over t h e pseudopotentials g i v i n g valence p s e u d o o r b i t a l s which a r e smooth i n t h e core r e g i o n . We have j u s t f i n i s h e d w r i t i n g a new MERGE technique which allows us t o r e t a i n t h e i n t e g r a l s f o r a s k e l e t a l fragment which remains unchanged. T h i s i s e s p e c i a l l y u s e f u l i n s t u d i e s o f l a r g e c l o s e l y r e l a t e d molecules and t h e i r complexes since only an atom or a few atoms are changed and except f o r t h e r i n g which i s being

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch020

20.

KAUFMAN

Ab-initio

E TA L .

Quantum

Chemical

423

Calculations

attacked, t h e s t r u c t u r e o f t h e r e s t o f t h e molecule remains i n v a r ­ i a n t . I t was not s t r a i g h t f o r w a r d t o i n c o r p o r a t e a MERGE t e c h n i ­ que i n t o our program s i n c e we c a l c u l a t e i n t e g r a l s v e r y e f f i c i e n t l y by blocks r a t h e r than one by one. We are now u s i n g t h i s MERGE o p t i o n f o r a l l our c a l c u l a t i o n s since t h e systems we are i n v e s t i ­ g a t i n g at present are q u i t e l a r g e . The MERGE o p t i o n i s u s e f u l for l a r g e molecules (even one and two r i n g systems], and excep­ t i o n a l l y v a l u a b l e f o r l a r g e r molecules and where t h e part t o be v a r i e d i s small compared t o a l a r g e i n v a r i a n t s t r u c t u r a l fragment. As an example, while t h e s k e l e t a l i n t e g r a l s f o r b e n z o p y r e n e - 7 , 8 d i h y d r o d i o l (a 5 - r i n g aromatic proximate carcinogen) took 3 0 0 5 seconds (CDC 6 6 0 0 , 0 P T = 1 ) t o form t h e u l t i m a t e carcinogen benzo­ p y r e n e - 7 , 8 - d i h y d r o d i o l - 9 , 1 0 - e p o x i d e , t h e extra MERGE i n t e g r a l s for t h e oxygen with the r e s t o f t h e skeleton took o n l y 5 6 0 seconds (CDC 6 6 0 0 , 0 P T = 1 ) (57_) . Thus i t was computationally extremely t r a c t a b l e f o r us t o vary t h e stereochemistry o f t h e epoxide r i n g and i t s opening t o form an a t t a c k i n g agent. We have r e c e n t l y run a b - i n i t i o MODPOT/VRDDO/MERGE c a l c u l a ­ t i o n s on t h e a t t a c k of CH3 , t h e simplest u l t i m a t e carcinogen, on guanine f o r a t t a c k on t h e 0 ° and N7 p o s i t i o n s ( 5 8 ) using s e v e r a l d i f f e r e n t types o f CDC computers (CDC 6 6 0 0 and CYBER 1 7 5 ) with a v a r i e t y o f d i f f e r e n t operating systems (which d i d or d i d not support, f u l l 0 P T = 1 and 0 P T = 2 compilers at v a r i o u s t i m e s ) . Some idea o f comparative timings can be seen below. +

Times (minutes) necessary t o c a r r y out a b - i n i t i o M 0 D P 0 T / V R D D 0 and a b - i n i t i o MODPOT/VRDDO/MERGE c a l c u l a t i o n s Species

No. Atoms

No. B a s i s Fns.

Time (minutes) Integrals or S k e l e t a l Integrals

C,N,0

H

Guanine

11

5

1+9

Guanine + CH

12

8

56

MERGE Integrals

11.2

SCF

^ . 3

6.8

Δ

T

2.3*

5·0

0.9

1 · /

+

+

3

2.9

V

V

* CDC 6600 computer, FTN, 0 P T = 0 (The i n t e g r a l s run even ~75# f a s t e r under 0 P T = 1 or 0 P T = 2 on a CDC 6600 computer t h a t supports a f u l l 0 P T = 1 or 0 P T = 2 compiler.) t CDC 6600 computer, FTN, 0 P T = 2 Δ CDC 66ΟΟ computer, FTN, 0PT=1 V CYBER 1 7 5 , FTN, 0 P T = 1 # CYBER 1 7 5 , FTN, 0 P T = 2 An unusual behavior occurred i n t h e system CH-^"** + guanine (G). As t h e i n t e r n u c l e a r 0 or Ν t o Me d i s t a n c e approached 5 bohrs, there was a mixing o f e l e c t r o n i c c o n f i g u r a t i o n s . When we saw t h e e l e c t r o n i c c o n f i g u r a t i o n mixing, our experience with t h e theory and p r e v i o u s l a r g e s c a l e a b - i n i t i o c o n f i g u r a t i o n i n t e r -

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

424

COMPUTER-ASSISTED

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a c t i o n c a l c u l a t i o n s on ion-molecule r e a c t i o n s i n d i c a t e d t h e p h y s i c a l b a s i s had t o be due to the f a c t that while the r e a c t a n t s were CH^ " + G, at the d i s s o c i a t i o n asymptote t h e r e was a lower energy set of fragments C H 3 + G . When we i n i t i a t e d our c a l c u l a t i o n s the experimental IP o f guanine had never been r e p o r t e d . However, we knew t h e p h o t o e l e c t r o n s p e c t r a of DNA bases was being i n v e s t i g a t e d by Le Breton. We c a l l e d him and indeed the i o n i z a t i o n p o t e n t i a l of guanine, 8.3 eV (68), i s c o n s i d e r a b l y lower than that of C H 3 , 9.8 eV (69). Using our e f f i c i e n t MERGE technique the time consuming p a r t of computing a s e r i e s of higher s u b s t i t u t e d m a t a b o l i t e s o f a common skeleton or p o t e n t i a l energy surfaces as a f u n c t i o n of nuclear geometry now becomes t h e SCF r a t h e r than the i n t e g r a l s . S i n c e t h e Fock matrix elements corresponding t o t h e i n v a r i a n t s k e l e t a l i n t e g r a l s remain v i r t u a l l y unchanged (except f o r a s l i g h t dependence on o r t h o g o n a l i t y ) e i t h e r f o r a f a m i l y of s u b s t i t u t e d molecules or f o r a l a r g e molecule being attacked by a smaller s p e c i e s , we have d e r i v e d a new s t r a t e g y based on p a s s i n g through f o r t h e SCF, e i t h e r i n t r a - or i n t e r m o l e c u l a r , the Fock matrix c o n t r i b u t i o n s from t h e i n v a r i a n t s k e l e t a l i n t e g r a l s making up o n l y the a d d i t i o n a l c o n t r i b u t i o n s t o the Fock matrix elements from t h e new i n t e g r a l s , a l l o w i n g o n l y t h e c o n t r i b u t i o n s from t h e new i n t e g r a l s t o the Fock m a t r i x elements t o change u n t i l the SCF c a l c u l a t i o n i s about converged, then r e l a x i n g and making up new Fock matrix elements from a l l of t h e i n t e g r a l s f o r each c y c l e u n t i l convergence. C o n s i d e r a b l e numerical t e s t i n g must now be done w i t h t h i s procedure.* I t i s expected t h a t t h i s technique w i l l work most e f f e c t i v e l y f o r systems where no convergence problems would otherwise be expected. I f the scheme works w e l l , we p l a n t o extend a s i m i l a r scheme t o do t r a n s f o r m a t i o n s o f i n t e g r a l s f o r CI c a l c u l a t i o n s f o r s e r i e s o f congeners or f o r c l o s e l y spaced p o i n t s along a p o t e n t i a l energy s u r f a c e . I n order t o o b t a i n convergence and compute at l e a s t the d i a b a t i c c o n t i n u a t i o n past 5 bohrs of t h e curve d e s c r i b i n g t h e c l o s e approach of CH3 t o guanine, we wrote new more e f f i c i e n t e x t r a p o l a t i o n and damping r o u t i n e s (70)» Both c l o s e d and o p e n - s h e l l systems can be c a l c u l a t e d . The programs can handle s e v e r a l hundred b a s i s f u n c t i o n s i n a CDC 6600 computer and more i n a CDC 7600. I n a d d i t i o n , we p l a n t o explore f u r t h e r new and n o v e l methods f o r subsequent c a l c u l a t i o n on l a r g e molecules the s i z e of block regions of DNA and f o r i n t e r a c t i o n of reagents with h e l i c a l DNA by molecular p a r t i t i o n i n g . 4

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch020

+

+

Configuration Interaction Calculations The M0DP0T/VRDD0 LCA0-M0-SCF programs have been meshed i n with t h e c o n f i g u r a t i o n i n t e r a c t i o n programs we use. In t h i s CI (71) program each c o n f i g u r a t i o n i s a s p i n - and symmetry-adapted l i n e a r combination of S l a t e r determinants i n the terms of t h e spin-bonded f u n c t i o n s of Boys and Reeves (72, 73 Jh) as formu?

9

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

20.

K A U F M A N E TA L .

Ab-initio

Quantum

Chemical

Calculations

425

l a t e d o r i g i n a l l y by S h a v i t t , Pipano and co-workers Ç75, 76, 77) and subsequently m o d i f i e d and extended i n our l a b o r a t o r y (78, 79,

80).

The determinants can be obtained from s i n g l e determinant or MC-SCF wave f u n c t i o n s . We have a l s o added a method o f c a l c u l a t i n g improved v i r t u a l o r b i t a l s . Our use o f t h i s procedure f o r N - e l e c t r o n e x c i t e d s t a t e v i r t u a l o r b i t a l s Ç81) i n the framework o f the SCF c a l c u l a t i o n o f the N - l e l e c t r o n problem c l o s e l y resembles those proposed by Huzinaga (82). We have a l s o i n v e s t i g a t e d Huzinaga s recent method f o r improved v i r t u a l o r b i t a l s i n the extended b a s i s f u n c t i o n space Ç83). T h i s i s a l s o a u s e f u l procedure where t h e r e a r e convergence problems f o r the Hartree-Fock c a l c u l a t i o n s f o r t h e N - e l e c t r o n occupied space o f t h e e x c i t e d s t a t e s . T h i s should a l s o be h e l p f u l i n o p t i m i z i n g v i r t u a l o r b i t a l s t o use them i n p e r t u r b a t i o n theory expressions. The most time and space consuming part and t h e l i m i t i n g f a c t o r o f a CI c a l c u l a t i o n i s the t r a n s f o r m a t i o n o f i n t e g r a l s from i n t e g r a l s over atomic b a s i s f u n c t i o n s t o i n t e g r a l s over molecular o r b i t a l s . We have implemented a technique which i n c o r p o r a t e s i n t o an e f f e c t i v e CI Hamiltonian operator t h e e f f e c t o f a l l molec u l a r o r b i t a l s from and t o which no e x c i t a t i o n s are made (Ok) .

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1

P e r t u r b a t i o n Procedures f o r Molecular I n t e r a c t i o n s I t would be d e s i r a b l e t o be a b l e t o c a l c u l a t e the m a j o r i t y o f the molecular i n t e r a c t i o n surface between l a r g e molecules by a p e r t u r b a t i o n technique r a t h e r than by the supermolecule technique. P r e v i o u s l y we had shown by comparison with accurate a b - i n i t i o c a l c u l a t i o n s t h e n o n - a p p l i c a b i l i t y o f the customary approximate m o n o p o l e - t r a n s i t i o n moment long range f o r c e expressions Ç86, 87) as w e l l as t h e n o n - a p p l i c a b i l i t y o f CNDO and INDO supermolecule p o t e n t i a l energy surfaces themselves f o r molecular i n t e r a c t i o n s even when the i n t e r a c t i n g supermolecule system i s c o r r e c t l y e x p r e s s i b l e by a s i n g l e determinant wave f u n c t i o n . The same a p p l i e s t o NDDO,MIND0 (88) , MNDO (8£, 20) and a l l other ZDO methods. Even worse, i n recent work presented on c a r c i n o g e n e s i s by others t h e MIND0/3 method (which was d e r i v e d t o d e s c r i b e s t a t i c thermochemistry) was used t o d e s c r i b e the r e a c t i o n pathway o f i n s e r t i o n o f s i n g l e t oxygen i n t o an R-H bond. F i r s t l y , no ZDO s i n g l e determinant method i s a p p r o p r i a t e even when the lowest energy surface o f the system separates c o r r e c t l y t o c l o s e d s h e l l ground s t a t e s p e c i e s . Secondly, the use of any s i n g l e determinant wave f u n c t i o n i s not c o r r e c t t o d e s c r i b e p o t e n t i a l energy surfaces f o r r e a c t i o n s o f t h i s 0 i n s e r t i o n t y p e , since there i s no way t h e lowest energy curve can d i s s o c i a t e c o r r e c t l y i n a s i n g l e determinant. T h i r d l y , t h e r e are f i v e s i n g l e t p o t e n t i a l energy surfaces a r i s i n g from 0 ^Dg + R-H which l i e lower i n energy a t the d i s s o c i a t i o n asymptote than the s i n g l e t p o t e n t i a l energy surface a r i s i n g from 0 -^S^ + R-H and a l l f i v e w i l l mix at some p o i n t s i n the p o t e n t i a l

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energy surfaces f o r t h e r e a c t i o n with t h e s i n g l e t surface a r i s i n g from 0 "^Sg + R-H. There i s no way t o d e s c r i b e such processes c o r r e c t l y except by a b - i n i t i o CI (or a b - i n i t i o MODPOT/VRDDO/CI or a b - i n i t i o M O D P O T / V R D D O / M E R G E / C I c a l c u l a t i o n s ) . A great prob­ lem (perhaps t h e g r e a t e s t ) i n e s t a b l i s h i n g and keeping t h e c r e d i ­ b i l i t y o f quantum chemical c a l c u l a t i o n s i n b i o l o g y and medicine i s t h e poor q u a l i t y of much o f t h e quantum chemical c a l c u l a t i o n s c a r r i e d out i n b i o l o g i c a l , pharmacological and medical a r e a s — and what i s even worse, i n c o r r e c t use o f quantum chemistry i n these areas. We are examining t h e question o f v a r i o u s r i g o r o u s p e r t u r b a ­ t i o n expressions ( 9 1 ) f o r i n t e r m o l e c u l a r i n t e r a c t i o n s and a r e c u r r e n t l y doing t h e a n a l y s i s and w r i t i n g a program t o c a l c u l a t e these (j?2) . We s h a l l t e s t t h e v a l i d i t y o f t h i s l a t t e r procedure by comparison with accurate a b - i n i t i o supermolecule c a l c u l a t i o n s for smaller t e s t systems. The e l e c t r o s t a t i c , exchange, charge-induced m u l t i p o l e , m u l t i pole-induced m u l t i p o l e , and c h a r g e - t r a n s f e r c o n t r i b u t i o n s can a l s o be c a l c u l a t e d by p a r t i t i o n i n g o f t h e SCF c a l c u l a t i o n . The d i s ­ p e r s i o n energy must be c a l c u l a t e d or estimated s e p a r a t e l y . We s h a l l a l s o g i v e c o n s i d e r a t i o n t o an a l t e r n a t i v e f o r m u l a t i o n f o r molecular i n t e r a c t i o n s f o r both s i n g l e determinant and m u l t i d e t e r minant wave f u n c t i o n s and t e s t these against a b - i n i t i o c a l c u l a ­ tions . In a d d i t i o n there a r e c o r r e l a t i o n energy terms ( A E r r ) "both i n t r a - and i n t e r - m o l e c u l a r . The l a r g e s t change i n i n t e r a c t i o n o f two non-polar molecules i s i n the i n t e r - m o l e c u l a r d i s p e r s i o n energy term r e s u l t i n g from the instantaneous p o l a r i z a t i o n o f A and B . Over t h e years v a r i o u s approximate formulas f o r i n t e r a c t i o n s between l a r g e molecules have been d e r i v e d from p e r t u r b a t i o n theory (91). The b e t t e r o f such p e r t u r b a t i o n theory expansions custom­ a r i l y i n c l u d e a short-range f i r s t order "exchange" term and long range terms ( e l e c t r o s t a t i c , p o l a r i z a t i o n and d i s p e r s i o n ) . Various approximations (such as the m u l t i - c e n t e r e d m u l t i p o l e expansion, r e p r e s e n t a t i o n o f t r a n s i t i o n d e n s i t i e s by bond d i p o l e and t h e decomposition o f molecular p o l a r i z a b i l i t y i n t o bond p o l a r i z a b i l i t i e s , t h e use o f atomic p o l a r i z a b i l i t i e s , bond-bond i n t e r a c t i o n terms, etc.) have been introduced f o r t h e c a l c u l a t i o n o f c e r t a i n of t h e terms. A c a r e f u l a n a l y s i s o f t h e SCF energy decomposition f o r an i n t e r - m o l e c u l a r i n t e r a c t i o n o f A and Β o f v a r i o u s p e r t u r b a t i o n energy expressions i n d i c a t e that f o r c e r t a i n p e r t u r b a t i o n formula­ t i o n s there i s a one-to-one correspondence between c e r t a i n SCF energy decomposition terms and c e r t a i n terms i n t h e p e r t u r b a t i o n expressions. Thus one can c a l c u l a t e t h e values f o r t h e terms from energy decomposition o f a b - i n i t i o or a b - i n i t i o MODPOT/VRDDO SCF wave f u n c t i o n s and compare these t o t h e values f o r t h e same type term r e s u l t i n g from t h e p e r t u r b a t i o n theory expressions. Care must be taken t o c o r r e c t f o r p o s s i b l e b a s i s set incompleteness. C O

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ET AL.

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Quantum

Chemical

Calculations

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Once both t h e form o f t h e v a r i o u s p e r t u r b a t i o n theory terms and t h e approximations t h a t may be involved i n estimating these terms have been v a l i d a t e d by comparison with a b - i n i t i o MODPOT/ VRDDO c a l c u l a t i o n s , then the most a p p r o p r i a t e p e r t u r b a t i o n theory expressions can be used i n p r e l i m i n a r y c a l c u l a t i o n s o f i n t e r molecular i n t e r a c t i o n s f o r t h e v a r i o u s r e a c t a n t s . T h i s same p e r t u r b a t i o n theory approach i s capable o f d e s c r i b ing both i n t e r - and i n t r a - m o l e c u l a r i n t e r a c t i o n s .

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch020

E l e c t r o s t a t i c Molecular

P o t e n t i a l Contour Maps

For molecular i n t e r a c t i o n s i n v o l v i n g molecules having net charges or permanent d i p o l e s , u s e f u l i n f o r m a t i o n may be drawn by examination of t h e e l e c t r o s t a t i c p o t e n t i a l , a r i s i n g from one o f the p a r t n e r s , and by simple e l e c t r o s t a t i c c a l c u l a t i o n s , i n v o l v i n g a p o t e n t i a l and a s i m p l i f i e d d e s c r i p t i o n of t h e charge d i s t r i b u t i o n of t h e other molecule i n v o l v e d i n the i n t e r a c t i o n (£G, 9*0 · The e l e c t r o s t a t i c p o t e n t i a l V(r) g i v e s more d e t a i l e d and l e s s ambiguous information than a p o p u l a t i o n a n a l y s i s , being a f u n c t i o n computed i n t h e o v e r a l l molecular surrounding space. From t h e p o t e n t i a l d e f i n i t i o n , t h e f i r s t order i n t e r a c t i o n energy between the molecular charge d i s t r i b u t i o n and a p o i n t charge distribution i s W ( {r.} ) =

Zq(r.) V ( r . )

Such an expression has p r e v i o u s l y been used f o r comparative purposes, f o r t h e study o f i n t e r a c t i o n between two molecular s p e c i e s , by computing t h e e l e c t r o s t a t i c p o t e n t i a l of t h e f i r s t partner and by assuming some point charge model as r e p r e s e n t a t i v e of t h e charge d i s t r i b u t i o n of t h e second p a r t n e r . We a l s o p l a n t o extend t h i s concept i n a more s u b t l e way by using an e l e c t r o n d e n s i t y contour map t o d e s c r i b e the charge d i s t r i b u t i o n o f t h e second p a r t n e r as a f u n c t i o n o f t h e space surrounding t h i s second partner. We were a b l e t o show t h a t a b - i n i t i o l a r g e b a s i s set and abi n i t i o optimized small b a s i s set wave f u n c t i o n s generate e l e c t r o s t a t i c molecular p o t e n t i a l contour maps almost i d e n t i c a l i n shape and magnitude (95). We a l s o confirmed t h e e a r l i e r f i n d i n g s by other r e s e a r c h e r s t h a t CNDO/2 and INDO wave f u n c t i o n s , e i t h e r orthogonal or deorthogonalized, d i d not generate maps which compared c o r r e c t l y with those generated from a b - i n i t i o wave f u n c t i o n s (95, 96, 97)* Those CNDO/2 and INDO maps a r e e s p e c i a l l y i n a c c u r a t e for aromatic compounds and even f o r i s o l a t e d double bonds (jté, 9 7 ) · Such maps a r e r e f l e c t i v e of dynamic r e a c t i o n i n d i c e s and prove more accurate i n d i c a t o r s o f t h e p o s i t i o n s favored f o r e l e c t r o p h i l i c a t t a c k than do such s t a t i c i n d i c e s as charges on t h e atoms.

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Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch020

Abstract The optimal strategy for ab-initio quantum chemical calculations on large molecules (drugs, carcinogens, teratogens and biomolecules) is somewhat different than for smaller molecules. It is possible to take advantage of certain computational properties of large molecules and of series of closely related congeners of large molecules. We have implemented several desirable options into our fast ab-initio Gaussian integral programs (SCF, MC-SCF and CI): the use of ab-initio effective core model potentials (MODPOT) which enable one to calculate only the valence electrons explicitly yet accurately, a charge conserving integral prescreening evaluation (VRDDO) especially effective for spatially extended molecules and a new MERGE technique which enables reuse of integrals from a common skeletal fragment and only recalculation of integrals involving new positions of certain atoms or new atoms. We have also recently derived a new SCF strategy which passes through Fock matrix elements as a starting Fock matrix, reutilizes the Fock matrix elements from the common skeletal integrals, takes advantage of the fact that the common Fock matrix elements change little during the preliminary iterations. We have also derived new MC-SCF and CI integral transformation strategies which take advantage of behavior similar to that utilized above. Examples are given from our recent research. Supported in part by NCI Contract NO1-CP-75929 and by NINCDS Contract NO1-NS-5-2320.

Ac kno wledgment T h i s r e s e a r c h was supported i n p a r t by NCI under Contract NOl-CP-75929. We thank our NCI contract monitor, Dr. Kenneth Chu, f o r h i s perceptiveness i n a p p r e c i a t i n g t h e c o n t r i b u t i o n s quantum chemical s t u d i e s could make t o t h e f i e l d o f chemical carcinogenesis. T h i s r e s e a r c h was supported i n p a r t by NINCDS under c o n t r a c t N01-NS-5-2320. We thank our NINCDS contract monitor, Dr. E r n s t Freese, f o r h i s a p p r e c i a t i o n o f t h e fundamental i n s i g h t quantum chemical c a l c u l a t i o n s , both i n t r a - and i n t e r - m o l e c u l a r , could make t o t h e processes l e a d i n g t o t e r a t o g e n e s i s and t o t h e general problems of membrane t r a n s p o r t and biomolecular i n t e r actions. We a l s o thank CDC f o r a grant o f CYBER 175 computer time. The timings f o r a b - i n i t i o MODPOT/VRDDO/MERGE c a l c u l a t i o n s on CH3 + guanine u s i n g t h e CYBER 175 a r e v e r y encouraging f o r t h e f u t u r e o f a b - i n i t i o c a l c u l a t i o n s on l a r g e drugs and biomolecules as w e l l as on carcinogens and teratogens. +

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

20. KAUFMAN ET AL.

Ab-initio Quantum Chemical Calculations

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46.

Popkie, Η. Ε., and Kaufman, Joyce J., "Test of Charge Con­ serving Integral Approximations for a Variable Retention of Diatomic Differential Overlap (VRDDO) Procedure for Semi Ab­ -Initio Molecular Orbital Calculations on Large Molecules," Int. J . Quantum Chem.: Quantum Biology Symp. (1975), 2, 279-288. 47. Kaufman, Joyce J., "Quantum Chemical Calculations on Small, Medium and Large Molecules," Presented at the Summer Conf. in Theoretical Chemistry, Boulder, Colorado, June 1975. 48. Popkie, Η. Ε., and Kaufman, Joyce J., "Molecular Calculations with the VRDDO, MODPOT and MODPOT/VRDDO Procedures. I. HF, F , HC1, Cl , Formamide, Pyrrole, Pyridine and Nitrobenzene," Int. J. Quantum Chem. Symp. Issue (1976), 10, 47-57. 49. Popkie, H. E., and Kaufman, Joyce J., "Molecular Calculations with the VRDDO, MODPOT and MODPOT/VRDDO Procedures. II. Cyclopentadiene, Benzene, Diazoles, Diazines and Benzonitrile," J. Chem. Phys. (1977), 66, 4827-4831. 50. Popkie, H. E., and Kaufman, Joyce J., "Molecular Calculations with the MODPOT, VRDDO and MODPOT/VRDDO Procedures. III. M0DPOT/SCF + CI Calculations to Determine Electron Affinities of Alkali Metal Atoms," Chem. Phys. Letts. (1977), 47, 55-58. 51. Kaufman, Joyce J., Popkie, H. E . , and Preston, H. J . T., "Ab-initio and Approximately Rigorous Calculations on Small, Medium and Large Molecules," Int. J. Quantum Chem. (1977), 11, 1005-1015. 52. Popkie, H. E., and Kaufman, Joyce J., "Molecular Calculations with the MODPOT, VRDDO and MODPOT/VRDDO Procedures. IV. Boron Hydrides and Carboranes," Int. J. Quantum Chem. (1977), 12, 937-961. 53. Popkie, Η. Ε., and Kaufman, Joyce J., "Molecular Calculations with the MODPOT, VRDDO and MODPOT/VRDDO Procedures. V. Ab-initio and MODPOT LCAO-MO-SCF Calculations on the Chlorofluoromethanes," Int. J . Quantum Chem. (1977), S11, 433-443. 54. Kaufman, Joyce J., and Popkie, H. E., "Molecular Calculations with Non-Empirical Ab-initio MODPOT, VRDDO and MODPOT/VRDDO Procedures. VI. Nucleic Acid Constituents: A, G, C, T," Presented at the Sixth Canadian Conference on Theoretical Chemistry, Fredericton, Ν. Β., Canada, June 1977. Manuscript in preparation for publication. 55. Kaufman, Joyce J., Popkie, H. E., and Preston, H. J . T., "Molecular Calculations with the Non-Empirical Ab-initio MODPOT, VRDDO and MODPOT/VRDDO procedures. VII. Prototype Normal Neurotransmitters and Their Metabolites," Presented at the Sixth Canadian Conference on Theoretical Chemistry, Fredericton, Ν. Β., Canada, June 1977. 56. Kaufman, Joyce J., Popkie, H. E., and Preston, H. J . T., "Molecular Calculations with the Ab-initio Non-Empirical MODPOT, VRDDO and MODPOT/VRDDO Procedures. VIII. Charge Derealization in the Anions of Aromatic Carboxylic Acids and Phenolic Compounds," Int. J . Quantum Chem. (1978), S12, 283291.

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Ab-initio Quantum Chemical Calculations

57. Kaufman, Joyce J., Popkie, H. E., Palalikit, S., and Hariharan, P. C., "Molecular Calculations with the Ab-initio Non­ -Empirical MODPOT, VRDDO and MODPOT/VRDDO Procedures. IX. Carcinogenic Benzo(a)pyrene and Its Metabolites Using a MERGE Technique," Int. J . Quantum Chem. (1978), 14, 793-800. 58. Hariharan, P. C., Popkie, H. E., and Kaufman, Joyce J., "Molecular Calculations with the Ab-initio Non-Empirical MODPOT, VRDDO, and MODPOT/VRDDO Procedures. X. The Attack of the Simplest Ultimate Carcinogen, CH3 , on Guanine by a MERGE Technique and the Fundamental Difference Between Methylating versus Ethylating Carcinogens," Presented at the Sanibel International Symposium on Quantum Biology and Quan­ tum Chemistry, Palm Coast, Florida, March 1979. In press Int. J. Quantum Chem.: Quantum Biology Symp. Issue. 59. Bonifacic, V., and Huzinaga, S., J . Chem. Phys. (1974), 60, 2779. 60. Ibid., J . Chem. Phys. (1975), 62, 1507. 61. Ibid., J . Chem. Phys. (1975), 62, 1509. 62. McWilliams, D., and Huzinaga, S., J . Chem. Phys. (1975), 63, 4678. 63. Huzinaga, S., personal discussion, August 1975. 64. Huzinaga, S., "Atomic and Molecular Calculations with Model Potential Method," Presented at the Quantum Chemistry Symposium, first North American Chemical Congress, Mexico City, December 1975. 65. Bonifacic, V., and Huzinaga, S., J . Chem. Phys. (1976), 64, 956. 66. Huzinaga, S., private communication, July 1977. 67. Kaufman, Joyce J., "potential Energy Surfaces for Ion-Mole­ cule Reactions," Presented at the NATO Advanced Study Insti­ tute on Ion-Molecule Reactions, La Baule, France, September 1978. In press in the Proceedings of the Meeting. 68. Le Breton, P. R., private communication, November 1978. 69. Rosenstock, Η. Μ., Draxl, K., Steiner, B. W., and Herron, J . T., J . Phys. Chem. Ref. Data (1977), 6, Supplement 1, 1-87. 70. Hariharan, P. C., The Johns Hopkins University, 1979. 71. Shavitt, I., "The Method of Configuration Interaction," in "Modern Theoretical Chemistry, Vol. II, Electronic Structure Ab-initio Methods," Ed. H. F. Schaefer, Plenum Press, New York, 1976. 72. Reeves, C. Μ., Ph.D. Thesis, Cambridge University, 1957. 73. Reeves, C . M . , Commun. ACM (Assoc. Comput. Mach.) (1966), 9, 276. 74. Cooper, I. L . , and McWeeny, R., J . Chem. Phys. (1966), 45, 226. 75. The basic CI programs described below are those written ori­ ginally by I. Shavitt and A. Pipano and continued by A. Pipano while he was a postdoctoral in our group at The Johns Hopkins University 1970-1971. In addition we have subse­ quently written a number of additional features to these CI programs 1971-present.

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76.

Gershgorn, Z., and Shavitt, I., Int. J. Quantum Chem. (1967), 1S, 403. 77. Pipano, Α., and Shavitt, I., Int. J . Quantum Chem. (1968), 2, 741. 78. Pipano, A., and Kaufman, Joyce J., The Johns Hopkins Univer­ sity, unpublished, 1971. 79. Preston, H. J . T., and Kaufman, Joyce J., The Johns Hopkins University, 1972-present. 80. Raffenetti, R. C., Preston, H. J . T., and Kaufman, Joyce J., The Johns Hopkins University, 1973. 81. Hunt, W. J., and Goddard, W. A., III, Chem. Phys. Letts. (1969), 3, 4l3. 82a. Huzinaga, S., and Arnau, C., Phys. Rev. (1970), A1, 1285. b. Huzinaga, S., and Arnau, C., J . Chem. Phys. (1971),54,1948. c. Hirao, Κ., and Huzinaga, S., Chem. Phys. Letts. (1977), 45, 55. 83. Huzinaga, S., and Hirao, K., J . Chem. Phys. (1977), 66, 2157. 84a. Raffenetti, R, C., The Johns Hopkins University, 1973. b. Raffenetti, R. C., ICASE, 1974-1976. 85. Kaufman, Joyce J., and Predney, R., "Non-Applicability for the Li - H Ion Molecule System of an INDO Potential Surface or of the Approximate Monopole-Transition Moment Long Range Force Expressions," Int. J . Quantum Chem. 5, 235. 86a. Rein, R., and Pollak, M., J. Chem. Phys. (1967), 47, 2039. b. Pollak, M., and Rein, R., J . Chem. Phys. (1967), 47, 2045. c. Rein, R., Claverie, P., and Pollak, Μ., Int. J . Quantum Chem. (1968), 2, 129. d. Claverie, P., and Rein, R., Int. J . Quantum Chem. (1969), 3, 537. 87. Pullman, Β., Claverie, P., and Caillet, J., Proc. Natl. Acad. Sci. USA (1966), 55, 911. 88. Dewar, M. J. S., and Dougherty, R. C., "The PMO Theory of Organic Chemistry," Plenum Publishing Corp., New York, 1975. 89. Dewar, M. J . S., and Thiel, W., J . Am. Chem. Soc. (1977), 99, 4899. 90. Ibid., (1977), 99, 4970. 91. Claverie, P., "Elaboration of Approximate Formulas for the Interactions Between Large Molecules: Applications in Organic Chemistry," in "Intermolecular Interactions: From Diatomic to Biopolymers," 69-305, Ed. B. Pullman, John Wiley and Sons, New York, 1978. (This review is extensive and contains several hundred references covering both rigor­ ous and approximate treatments.) 92. Sokalski, W. Α., Hariharan, P. C., and Kaufman, Joyce J., The Johns Hopkins University, research in progress, 1979. 93. Scrocco, E . , and Tomasi, J., Top. Curr. Chem. (1973), 21, 97, and references therein. 94. Petrongolo, C., Gazz. Chim. Ital. (1978), 108,445,and references therein. 95. Petrongolo, C., Preston, H. J . T., and Kaufman, Joyce J., +

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Ab-initio Quantum Chemical Calculations

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"Ab-initio LCAO-MO-SCF Calculations of the Electrostatic Molecular Potential of Chlorpromazine and Promazine," Int. J. Quantum Chem. (1978), 13, 457-468. 96, Kaufman, Joyce J., "Recent Physicochemical and Quantum Chemical Studies on Drugs of Abuse and Relevant Biomolecules," in "Quantitative Structure Activity Relationships of Analgesics, Narcotic Antagonists and Hallucinogens," 250-277, Eds. G. Barnett, M. Trsic and R. E. Willette, NIDA Research Monograph 22, DHEW, NIDA, 1978. 97. Petrongolo, C., Preston, H. J. T., Popkie, H. E . , and Kaufman, Joyce J., The Johns Hopkins University, 1975-1978. RECEIVED

June 8, 1979.

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21 Application of C N D O / 2 Calculations and X-Ray Crystallographic Analysis to the Design of Conformationally Defined Analogs of Methamphetamine GARY L. GRUNEWALD, MARY WEIR CREESE, and D. ERIC WALTERS Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

Department of Medicinal Chemistry, University of Kansas, Lawrence, KS 66045 A major objective of our research program is to elucidate the molecular events involved i n the i n t e r action of sympathomimetic amines with the adrenergic neuroeffector complex. A major portion of t h i s work i s aimed at the delineation of the conformational r e q u i r e ments for optimal i n t e r a c t i o n of sympathomimetic amines with t h e i r various p h y s i o l o g i c a l l y s i g n i f i c a n t i n t e r active s i t e s within the synaptic area (pre- and post-synaptic receptors, presynaptic uptake and storage s i t e s and metabolic enzymes). Such knowledge would be p r e r e q u i s i t e for r a t i o n a l design of s p e c i f i c chemical agents to s e l e c t i v e l y modify neurotransmitter-receptor interactions and to eventually replace drugs of less specificity. Any discussion of s t r u c t u r e - a c t i v i t y r e l a t i o n s h i p s among sympathomimetic amines must be undertaken i n terms of the m u l t i p l i c i t y of p h y s i o l o g i c a l l y important s i t e s within the noradrenergic synapse with which such amines can p o t e n t i a l l y i n t e r a c t . A generalized synapse of t h i s type i s depicted i n Figure 1, and consists of the following generally accepted points of molecular physiology. Consider first the presynaptic events. Depolarization of the nerve ending r e s u l t s i n elevated i n t r a neuronal Ca l e v e l s and concomitant exocytotic release of norepinephrine from the storage granule (1,2,3) where norepinephrine i s stored i n high concentrations as an osmotically i n e r t complex with ATP (4,5). ++

A l t h o u g h most n e u r o n a l n o r e p i n e p h r i n e e x i s t s i n t h i s v e s i c u l a r pool, there i s also a small e x t r a v e s i c u l a r p o o l which has been i n t e r p r e t e d i n terms o f n o r e p i n e p h r i n e i o n i c a l l y bound t o s o l u b l e c y t o p l a s m i c c o n s t i t u e n t s ((5) . The c y t o p l a s m i c p o o l o f n o r e p i n e p h r i n e i n f a c t i s m a i n t a i n e d a t i t s low l e v e l by v e s i c u l a r s t o r a g e o f n o r e p i n e p h r i n e and by o x i d a t i v e d e a m i n a t i o n 0-8412-0521-3/79/47-112-439$ 12.25/0 © 1979 A m e r i c a n C h e m i c a l Society

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

COMPUTER-ASSISTED DRUG DESIGN

Figure 1.

The noradrenergic nerve ending

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

21.

GRUNEWALD E T A L .

Analogs

of

Methamphetamine

441

of n o r e p i n e p h r i n e v i a m i t o c h o n d r i a l monoamine o x i d a s e (MAO). Thus, i n h i b i t i o n o f MAO (pargyline) provides a means o f s w e l l i n g the e x t r a v e s i c u l a r n o r e p i n e p h r i n e compartment (7). The v e s i c u l a r p o o l can be o b l a t e d a l t o g e t h e r by t r e a t m e n t w i t h r e s e r p i n e which i r r e v e r ­ s i b l y i n h i b i t s the v e s i c u l a r uptake o f n o r e p i n e p h r i n e (*L'D · While d e p o l a r i z a t i o n r e l e a s e s o n l y v e s i c u l a r n o r e p i n e p h r i n e i n a C a - d e p e n d e n t manner (10), i n d i r e c t l y a c t i n g sympathomimetic agents w i l l d i s p l a c e n o r e p i n e p h r i n e from both s t o r a g e forms i n a Ca independent manner (11,12). Norepinephrine r e l e a s e d i n t o the s y n a p t i c area i s r e n d e r e d i n a c t i v e e i t h e r by O - m e t h y l a t i o n (primarily meta but some para) v i a c a t e c h o l O - m e t h y l t r a n s f e r a s e (13) o r by uptake by the n e u r o n a l amine uptake system. U t i l i z i n g the i n w a r d l y - d i r e c t e d N a c o n c e n t r a t i o n g r a d i e n t m a i n t a i n e d by the n e u r o n a l membrane ( N a + K ) ATPase, n o r e p i n e p h r i n e i s c o - t r a n s p o r t e d w i t h N a in a f a c i l i t a t e d d i f f u s i o n p r o c e s s which appears t o be c a r r i e r - m e d i a t e d (14 ,l!p) . I n h i b i t o r s o f (Na + Κ )-ATPase w i l l a n t a g o n i z e n o r e p i n e p h r i n e a c c u m u l a t i o n as w i l l sympathomimetic amines which c o m p e t i t i v e l y b i n d t o the uptake c a r r i e r (15). C o c a i n e and d e s i p r a m i n e (DMI) b o t h d i s p l a y a h i g h a f f i n i t y f o r the c a r r i e r system, thus i n h i b i t i n g the uptake o f n o r e p i n e p h r i n e . P o s t s y n a p t i c a l l y n o r e p i n e p h r i n e may i n t e r a c t w i t h a- o r β-receptors, which c o u p l e w i t h an a d e n y l a t e (or guanylate) c y c l a s e t o i n i t i a t e p o s t s y n a p t i c events (16,17). P r e s y n a p t i c a- and β-receptors have a l s o been i m p l i c a t e d i n the m o d u l a t i o n o f t r a n s m i t t e r r e l e a s e . While an a d e n y l a t e c y c l a s e has been a s s o c i a t e d w i t h the p r e s y n a p t i c β-receptor, the p r e s y n a p t i c α-receptor appears t o be i n v o l v e d o n l y w i t h m o d u l a t i o n o f C a f l u x e s (18,19). S t r u c t u r e - a c t i v i t y r e l a t i o n s h i p s (SAR) i n sympa­ thomimetic amines must then d e a l w i t h t h e e f f e c t o f m o l e c u l a r s t r u c t u r e on: 1) The i n h i b i t i o n o f n e u r o n a l t r a n s m i t t e r uptake. 2) The uptake and r e t e n t i o n o f the agents them­ selves . 3) The r e l e a s e o f t r a n s m i t t e r from i t s s t o r a g e sites. 4) D i r e c t r e c e p t o r a c t i v i t y o f the amines. 5) C o m p e t i t i v e b i n d i n g t o the a c t i v e s i t e s o f m e t a b o l i c enzymes. Unless these e f f e c t s are c a r e f u l l y s o r t e d out, e f f o r t s to d e s i g n s e l e c t i v e agents a r e thwarted from the outset. A r e v i e w o f SAR w i t h i n each d i v i s i o n o f a c t i o n would be i m p o s s i b l e w i t h i n the c o n f i n e s o f the p r e s e n t

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discussion. The r e a d e r i s r e f e r r e d elsewhere f o r t h e g e n e r a l c o n c l u s i o n s o f SAR on t h e c o m p e t i t i v e i n h i b i t i o n o f t h e n e u r o n a l uptake o f n o r e p i n e p h r i n e (20,21, 221,23) , t r a n s p o r t o f n o r e p i n e p h r i n e by t h e c a r r i e r (24TT r e l e a s e o f p r e v i o u s l y accumulated n o r e p i n e p h r i n e (25), i n t e r a c t i o n o f d i r e c t l y - a c t i n g sympathomimetic a g o n i s t s on t h e a - and 3 - r e c e p t o r s (26) and t h e subs t r a t e s p e c i f i c i t y f o r catechol O-methyltransferase (2J_,20). These c o n c l u s i o n s o f SAR i l l u s t r a t e t h a t s e l e c t i v i t y o f p h a r m a c o l o g i c a l a c t i o n i s n o t always p o s s i b l e through gross s t r u c t u r a l manipulation alone. S e v e r a l i n t e r a c t i v e s i t e s can d i s p l a y s i m i l a r s t r u c t u r a l preference. D e s p i t e t h e d e t a i l o f t h e s e SAR s t u d i e s , t h e e x a c t n a t u r e o f t h e n e u r o t r a n s m i t t e r (or d r u g ) r e c e p t o r complex remains unknown. The p o s s i b i l i t y t h a t d i f f e r e n t s i t e s o f drug a c t i o n r e q u i r e d i f f e r e n t c o n f o r m a t i o n a l arrangements o f t h e a g o n i s t , t h e r e b y u n c o v e r i n g a new dimension o f drug s e l e c t i v i t y n o t p o s s i b l e through g r o s s s t r u c t u r a l m a n i p u l a t i o n a l o n e , w i l l be d i s c u s s e d below. Techniques f o r A s s e s s i n g C o n f o r m a t i o n - A c t i v i t y Relationships Conformation-activity r e l a t i o n s h i p s are c o n s i d e r a b l y more d i f f i c u l t t o d e l i n e a t e than a r e structure-activity relationships. In the l a t t e r case, one needs o n l y t o modify t h e s t r u c t u r e o f an a c t i v e s u b s t a n c e and t o d e t e r m i n e t h e p h a r m a c o l o g i c a l e f f e c t s i n d u c e d by t h e s t r u c t u r a l change. Most a c t i v e a d r e n e r g i c a g e n t s , however, a r e c o n f o r m a t i o n a l l y m o b i l e ; r o t a t i o n about s i n g l e bonds i s u s u a l l y f a c i l e and r a p i d . F o r t h i s r e a s o n , most a d r e n e r g i c agents provide very l i t t l e d i r e c t information regarding conformational e f f e c t s . A number o f t e c h n i q u e s have been a p p l i e d t o t h e study o f c o n f o r m a t i o n - a c t i v i t y r e l a t i o n s h i p s : x-ray c r y s t a l structure determination, molecular o r b i t a l c a l c u l a t i o n s o f low-energy c o n f o r m a t i o n s , n u c l e a r magnetic resonance d e t e r m i n a t i o n s o f s o l u t i o n c o n f o r m a t i o n s , and t h e p r e p a r a t i o n o f c o n f o r m a t i o n a l l y r e s t r i c t e d analogs. The f i r s t t h r e e methods a r e d i r e c t e d toward d e t e r m i n i n g which c o n f o r m a t i o n (or which c o n f o r m a t i o n s ) i s (are) most f a v o r a b l e ; t h e assumption i s made t h a t an e n e r g e t i c a l l y p r e f e r r e d c o n f o r m a t i o n w i l l be t h e b i o l o g i c a l l y a c t i v e c o n f o r mation. T h i s need n o t be t h e c a s e ; P o r t o g h e s e ' s s u g g e s t i o n (29) r e g a r d i n g a " h i g h - e n e r g y " c o n f o r m a t i o n would n o t be c o n s i s t e n t w i t h such an assumption. Nevertheless, the p o s s i b i l i t y that a favorable

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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Methamphetamitie

443

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c o n f o r m a t i o n might c o r r e s p o n d t o an a c t i v e one has s e r v e d as a s t a r t i n g p o i n t f o r a l a r g e amount o f research. The use o f c o n f o r m a t i o n a l l y - r e s t r i c t e d a n a l o g s p r e c l u d e s t h e n e c e s s i t y o f such an assumption, but t h i s method a l s o has i t s l i m i t a t i o n s . We w i s h t o combine a number o f t h e s e t e c h n i q u e s i n a s i n g l e l a b o r a t o r y w i t h t h e hope t h a t t h e advantages o f each approach w i l l be m a g n i f i e d and t h e d i s a d v a n t a g e s minimized. X-Ray C r y s t a l l o g r a p h y . T h i s approach i s based on the assumption t h a t a low-energy c o n f o r m a t i o n s h o u l d be the c o n f o r m a t i o n r e c o g n i z e d by t h e r e c e p t o r . (Receptor i s here used l o o s e l y t o r e f e r t o any s i t e o f i n t e r ­ a c t i o n w i t h t h e a g o n i s t o r a n t a g o n i s t m o l e c u l e ) . The c r y s t a l l i n e form o f a s u b s t a n c e s h o u l d c e r t a i n l y be a r e l a t i v e l y low-energy and s t a b l e c o n f o r m a t i o n . I n a d d i t i o n , s t r u c t u r a l and c o n f o r m a t i o n a l f e a t u r e s a r e d e l i n e a t e d w i t h a h i g h degree o f a c c u r a c y by x - r a y diffraction. S e v e r a l n e g a t i v e f a c t o r s s h o u l d be p o i n t e d o u t , however. F i r s t , t h e m o l e c u l e i n t h e s o l i d s t a t e has a much d i f f e r e n t environment from t h a t in dilute solution. A l s o , i f a s u b s t a n c e has two o r more r e l a t i v e l y s t a b l e c o n f o r m a t i o n s , o n l y one o f t h e s e i s l i k e l y t o e x i s t i n the c r y s t a l , while the other(s) would go u n d e t e c t e d . F i n a l l y , c r y s t a l packing forces may cause d i s t o r t i o n s o f t h e m o l e c u l e whenever t h e i n c r e a s e d s t r a i n energy i s compensated f o r by enhanced intermolecular interactions. A t l e a s t e i g h t e e n p h e n y l e t h y l a m i n e s have been examined by x - r a y c r y s t a l l o g r a p h y . Among t h e s e a r e p h e n y l e t h y l a m i n e h y d r o c h l o r i d e (30) , e p h e d r i n e h y d r o ­ c h l o r i d e (31), e p h e d r i n e monohydrogen phosphate monohydrate (32) , e p h e d r i n e d i h y d r o g e n phosphate (33) , dopamine h y d r o c h l o r i d e (34) , 5-hydroxydopamine h y d r o ­ c h l o r i d e (35,) , 6-hydroxydopamine h y d r o c h l o r i d e (36.) / e p i n e p h r i n e hydrogen t a r t r a t e (37) , n o r e p i n e p h r i n e h y d r o c h l o r i d e (38), i s o p r o t e r e n o l s u l f a t e (39) , 2,4,5trimethoxyamphetamine h y d r o c h l o r i d e (40), 4 - e t h y l - 2 , 5 dimethoxyamphetamine (41) , m e s c a l i n e hydrobromide ( 4 2 ) , and m e s c a l i n e h y d r o c h l o r i d e ( 4 3 ) . U s i n g t h e c o n v e n t i o n s shown i n F i g u r e 2, s e v e r a l o b s e r v a t i o n s may be made r e g a r d i n g t h e s o l i d s t a t e conformations o f these phenylethylamines. First, f i f t e e n o f t h e e i g h t e e n compounds have t h e n i t r o g e n atom and t h e a r o m a t i c r i n g i n an extended c o n f o r m a t i o n (ΤΛ = 180°). I t i s i n t e r e s t i n g t o note t h a t m e s c a l i n e h y d r o c h l o r i d e e x i s t s i n an extended c o n f o r m a t i o n , w h i l e t h e hydrobromide has a gauche c o n f o r m a t i o n . S i n c e t h e i o n i c r a d i i o f t h e a n i o n s (44) a r e v e r y

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

444

Figure 2. 2-Phenylethyhmine (unless otherwise stated, the numbering system shown is used throughout most of this paper in describing phenylethylamines)

6'

t

2 t

2

N u m b e r of observations 3η

2H

0

30

Figure 3.

60

90

120

150

Distribution of values of TJ (see text)

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

180

21.

GRUNEWALD E T A L .

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

—

Analogs

of Ο

Methamphetamine _

445

Ο

n e a r l y e q u a l ( C l = 1 . 8 0 A; Br = 1 . 9 5 A ) , i t would appear t h a t b o t h c o n f o r m a t i o n s a r e r e a s o n a b l y s t a b l e and might e x i s t i n d i l u t e s o l u t i o n . Among t h e t h r e e compounds e x i s t i n g i n a gauche c o n f o r m a t i o n ( τ ^ = 6 0 ° ) , m e s c a l i n e hydrobromide and 2 , 4 , 5 - t r i methoxyamphetamine h y d r o c h l o r i d e a r e p o t e n t h a l l u ­ cinogens , while 4-ethyl-2,5-dimethoxyamphetamine i s r e p o r t e d t o cause e u p h o r i a and a f e e l i n g o f enhanced self-awareness ( 4 5 ) . In F i g u r e 3 , t h e T]_ v a l u e s a r e r e p r e s e n t e d graphically. I t may be seen t h a t most o f t h e s e v a l u e s f a l l i n t h e range o f 6 7 ° t o 9 7 ° , i n d i c a t i n g t h a t t h e s i d e c h a i n i s u s u a l l y d i r e c t e d away from the p l a n e o f t h e a r o m a t i c r i n g . The two e x c e p t i o n s a r e 5-hydroxydopamine ( 5 9 ° ) and e p i n e p h r i n e hydrogen tartrate ( 1 7 9 ° ) . In the l a t t e r case, the authors ( 3 7 ) suggest t h a t t h e e x t r e m e l y dense p a c k i n g o f the s t r u c t u r e and t h e numerous hydrogen bonds may cause t h e m o l e c u l e t o assume t h i s u n u s u a l c o n f o r m a t i o n . Molecular O r b i t a l Calculations. Theoretical c a l c u l a t i o n s o f m o l e c u l a r p r o p e r t i e s have become r e a s o n a b l y a c c u r a t e and r e l a t i v e l y easy t o c a r r y o u t i n r e c e n t y e a r s . Atomic c o o r d i n a t e s from x - r a y s t r u c t u r e d e t e r m i n a t i o n s o r s t a n d a r d bond l e n g t h s and a n g l e s can s e r v e as t h e i n p u t , and a wide range o f p r o p e r t i e s may be d e t e r m i n e d . Of p a r t i c u l a r i n t e r e s t t o us i s t h e d e t e r m i n a t i o n o f t h e r e l a t i v e e n e r g i e s of v a r i o u s conformations o f a molecule, or the r e l a t i v e p o p u l a t i o n s o f a s e r i e s o f conformers. Rotational b a r r i e r s , which can a f f e c t i n t e r c o n v e r s i o n among c o n f o r m e r s , can a l s o be e s t i m a t e d . The assumption i s a g a i n made t h a t a c o n f o r m a t i o n which predominates i n s o l u t i o n s h o u l d be b i o l o g i c a l l y a c t i v e . Other parameters (such as charge d i s t r i b u t i o n ) which r e f l e c t the c a p a c i t y f o r e l e c t r o s t a t i c i n t e r a c t i o n s a t v a r i o u s p o i n t s on t h e m o l e c u l e can be c a l c u l a t e d . F i v e c o m p u t a t i o n a l methods have been a p p l i e d t o conformational studies of phenylethylamines. These a r e Extended Hiickel Theory (EHT) ( £ 6 ) , Complete N e g l e c t o f D i f f e r e n t i a l O v e r l a p (CNDO) ( 4 7 ) , I n t e r m e d i a t e N e g l e c t o f D i f f e r e n t i a l O v e r l a p (INDOl ( £ 8 ) , P e r t u r b a t i v e Configuration Interactions using Localized Orbitals (PCILO) ( £ 9 ) , and some ab i n i t i o (ΑΙ) ( 5 Ό ) p r o c e d u r e s . EHT i s r e l a t i v e l y easy and i n e x p e n s i v e t o u s e , b u t i t tends t o d i s t o r t e l e c t r o n d i s t r i b u t i o n i n systems c o n t a i n i n g heteroatoms. I n EHT, e l e c t r o n - r e p u l s i o n terms a r e n e g l e c t e d , c a u s i n g a tendency t o p r e d i c t u n r e a l i s t i c a l l y low e n e r g i e s f o r gauche and e c l i p s e d conformations. CNDO and INDO t a k e i n t o account some

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

446

DRUG DESIGN

i m p o r t a n t e l e c t r o n - r e p u l s i o n terms, b u t gauche and e c l i p s e d c o n f o r m a t i o n s a r e a g a i n p r e d i c t e d t o be t o o stable r e l a t i v e t o staggered conformations. CNDO and INDO a r e r e f e r r e d t o as " s e m i - e m p i r i c a l " because t h e y can be " p a r a m e t e r i z e d " ; c e r t a i n v a r i a b l e s i n t h e computation a r e a s s i g n e d v a l u e s which w i l l g i v e good r e s u l t s f o r a g i v e n c l a s s o f compounds o r f o r a g i v e n c h e m i c a l p r o p e r t y . A l l o f t h e above methods e x c e p t PCILO employ t h e H a r t r e e - F o c k a p p r o x i m a t i o n i n t h e i r c a l c u l a t i o n s ; t h i s approximation i s v a l i d only a t o r near low-energy s t a t e s o f t h e m o l e c u l e . For this reason, r o t a t i o n a l b a r r i e r s are often overestimated. PCILO, on t h e o t h e r hand, p r e d i c t s s l i g h t l y l o w e r - t h a n normal r o t a t i o n a l b a r r i e r s . AI methods use much more s o p h i s t i c a t e d c o m p u t a t i o n s , b u t t h e b a s i s s e t s from which m o l e c u l e s a r e c o n s t r u c t e d a r e o f t e n e i t h e r t o o s m a l l t o g i v e good r e s u l t s o r t o o e x p e n s i v e t o use f o r m o l e c u l e s o f more t h a n a few atoms. A more mathe­ m a t i c a l comparison o f methods has been p r e s e n t e d by Hoyland (51.) . T a b l e I l i s t s t h e compounds which have been s t u d i e d by m o l e c u l a r o r b i t a l methods. T h i s l i s t i n c l u d e s d i r e c t l y and i n d i r e c t l y a c t i n g a g o n i s t s as w e l l as a n t a g o n i s t s . A l t h o u g h t h e e n e r g i e s d e t e r m i n e d by t h e s e methods a r e n o t f r e e e n e r g i e s s i n c e e n t r o p i e e f f e c t s a r e n o t t a k e n i n t o c o n s i d e r a t i o n , energy d i f f e r e n c e s among c l o s e l y r e l a t e d compounds appear t o be q u i t e a c c u r a t e l y d e t e r m i n e d . Conformational r e s u l t s are often s e n s i t i v e t o the i n p u t geometry used. F o r i n s t a n c e , Pullman at at. (68) c a r r i e d o u t two PCILO c a l c u l a t i o n s f o r m e s c a l i n e , u s i n g the x-ray c r y s t a l geometries obtained f o r t h e hydrobromide and h y d r o c h l o r i d e s a l t s ; t h e s e s a l t s e x i s t i n gauche and extended c o n f o r m a t i o n s , r e s p e c t i v e l y . In b o t h c a s e s t h e c a l c u l a t i o n s showed r e l a t i v e minima f o r b o t h c o n f o r m a t i o n s , and t h e s e minima d i f f e r e d by l e s s than one k c a l / m o l . I n each c a s e , however, t h e g l o b a l ( o v e r a l l ) minimum c o r r e s p o n d e d t o t h e c r y s t a l geometry. M a r t i n zt at. (70) have p u b l i s h e d a d e t a i l e d s t u d y o f p h e n y l e t h y l a m i n e , u t i l i z i n g EHT, CNDO, INDO, PCILO and A I . These a u t h o r s used s e m i - e m p i r i c a l methods t o g e n e r a t e a s e r i e s o f c o n f o r m a t i o n a l energy s u r f a c e s and then used an AI p r o c e d u r e w i t h a l a r g e b a s i s s e t f o r a few s e l e c t e d p o i n t s . EHT, CNDO and INDO a l l i n d i c a t e d a minimum f o r T± a t 9 0 ° ; EHT p r e d i c t s a r o t a t i o n a l b a r r i e r o f 7 k c a l / m o l , w h i l e CNDO and INDO show a b a r r i e r o f about 2 k c a l / m o l . PCILO g i v e s a r o t a t i o n a l b a r r i e r o f about 2 k c a l / m o l , b u t i t shows a v e r y broad minimum f o r τ ι , r a n g i n g from 4 5 ° t o 1 3 5 ° . With r e s p e c t t o r o t a t i o n about τ , t h e s e a u t h o r s found t h e extended 9

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

21.

GRUNEWALD E T A L .

Analogs

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Methamphetamine

447

form t o be about 1 k c a l / m o l more s t a b l e than t h e gauche u s i n g EHT and Α Ι , w h i l e t h e gauche form appeard t o be about 1 k c a l / m o l more s t a b l e u s i n g CNDO, INDO and PCILO. The most e x t e n s i v e s t u d i e s o f p h e n y l e t h y l a m i n e s have been done by Pullman and coworkers (5>9,6J5,6T7,68) . T h e i r PCILO c a l c u l a t i o n s i n d i c a t e d t h a t gauche and t r a n s conformers have n e a r l y i d e n t i c a l e n e r g i e s i n t h e m a j o r i t y o f p h e n y l e t h y l a m i n e s and p h e n y l e t h a n o l a m i n e s studied. AI s t u d i e d were c a r r i e d o u t u s i n g t h r e e d i f f e r e n t b a s i s s e t s (67); t h e s e a l l i n d i c a t e d a s l i g h t b u t d e f i n i t e p r e f e r e n c e f o r gauche c o n f o r m e r s . These a u t h o r s n o t e d t h e preponderance o f extended conformers i n c r y s t a l s t r u c t u r e s and i n s o l u t i o n ; t h e y a t t r i b u t e d t h i s t o environmental f o r c e s . To t e s t t h i s h y p o t h e s i s , computations were r e p e a t e d w i t h t h e i n c l u s i o n o f water m o l e c u l e s , and a tendency toward the extended c o n f o r m a t i o n was i n d e e d o b s e r v e d . Thus, most o f t h e e v i d e n c e a v a i l a b l e from molecular o r b i t a l c a l c u l a t i o n s suggests t h a t both the extended and gauche c o n f o r m a t i o n s a r e r e a s o n a b l y s t a b l e . I t would appear unwise t o deduce t h a t one o f t h e s e c o n f o r m a t i o n s c a n be r e c o g n i z e d i n v i v o and t h e o t h e r n o t , s o l e l y on t h e b a s i s o f such c o m p u t a t i o n s . N u c l e a r M a g n e t i c Resonance. Through a c a r e f u l a n a l y s i s o f c o u p l i n g c o n s t a n t s , i t has sometimes been p o s s i b l e t o d e r i v e c o n f o r m a t i o n a l i n f o r m a t i o n from n u c l e a r magnetic resonance (NMR) s p e c t r a . This offers the advantage o f d i r e c t l y d e t e r m i n i n g s o l u t i o n c o n f o r ­ m a t i o n s , which s h o u l d be more r e l e v a n t t o t h e b i o ­ l o g i c a l s i t u a t i o n than would be s o l i d s t a t e o r i n vacuo c o n f o r m a t i o n s . Once a g a i n , t h e u n d e r l y i n g assumption i s t h a t a h i g h l y p o p u l a t e d conformer i s the a c t i v e s p e c i e s . T a b l e I I summarizes t h e c o n f o r ­ m a t i o n a l s t u d i e s o f p h e n y l e t h y l a m i n e s which have been c a r r i e d o u t u s i n g NMR. In d e s c r i b i n g conformations, we w i l l use t h e f o l l o w i n g c o n v e n t i o n s (see F i g u r e 4 ) : 1) 1^ w i l l d e s i g n a t e t h a t c o n f o r m a t i o n i n which the n i t r o g e n atom i s a n t i p e r i p l a n a r w i t h respect t o the aromatic r i n g . 2) II_ w i l l d e s i g n a t e t h a t c o n f o r m a t i o n i n which the a r o m a t i c r i n g and t h e n i t r o g e n atom a r e i n a gauche r e l a t i o n s h i p ; i n compounds b e a r i n g a h y d r o x y l group on C-2, 11^ w i l l a l s o have t h e n i t r o g e n and oxygen atoms gauche t o each o t h e r , and i n amphetamines, I_I w i l l have t h e C - l methyl group a n t i p e r i p l a n a r w i t h r e s p e c t t o the a r o m a t i c r i n g . 3) I I I w i l l d e s i g n a t e a gauche r e l a t i o n s h i p

American Chemical Society Library 1155 f6th St. N. W. In Computer-Assisted Drug Design; Olson, E., el al.; Washington, D. C. Society: 20036 ACS Symposium Series; American Chemical Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

448

T a b l e I . Summary o f m o l e c u l a r o r b i t a l

studies of

phenylethylamines.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

Compound(s)

Method

Ref.

1.

Ephedrine Pseudoephedrine

EHT

52

2.

Norepinephrine

EHT

53

3. Dopamine

EHT

54

4. Dopamine

EHT

55

Norepinephrine Epinephrine N-Ethylnorepinephrine Isoproterenol

EHT, CNDO

56

Norepinephrine Norepinephrine·Li-H20

INDO

57

7. Dopamine

EHT

58

8.

PCILO

59

PCILO

60

10. P r a c t o l o l 1-(4 -methylphenyl)-2-isopropylaminoethanol 1-(4'-methylphenyl)-2-isopropylaminopropanol

CNDO

61

11.

Dopamine

EHT

62

12.

Norepinephrine Dopamine ( i n c l u d i n g meta- and para-anions)

CNDO

63

Phenylethylamine Norepinephrine Ephedrine Dopamine Tyramine Norephedrine Epinephrine Amphetamine

9. P h e n o x y e t h y l a m i n e

1

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

21.

GRUNEWALD E T A L .

Analogs of

Methamphetamine

449

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

T a b l e I (cont'd.) 13.

2,5-Dihydroxyphenylethylamine 2.3.4- T r i h y d r o x y p h e n y l e t h y l a m i n e 3.4.5- T r i h y d r o x y p h e n y l e t h y l a m i n e 2.3.6- T r i h y d r o x y p h e n y l e t h y l a m i n e 2,4,6-Trihydroxyphenylethylamine

CNDO

64

14.

2,4,5-Trimethoxyamphetamine 2,4,6-Trimethoxyamphetamine

PCILO

65

15.

Norepinephrine

CNDO

66

16.

Norepinephrine Amphetamine Epinephrine Isoproterenol Ephedrine

AI, PCILO

67

17. M e s c a l i n e 2.3.4- Trimethoxyamphetamine 2.4.5- Trimethoxyamphetamine 2.4.6- Trimethoxyamphetamine 2,4,5-Trihydroxyphenylethylamine 3,4,5-Trihydroxyphenylethylamine

PCILO

68

18.

CNDO

69

AI EHT CNDO INDO PCILO

70

Isoproterenol INPEA

19.

Phenylethylamine

2 0.

Phenylethylamine Amphetamine

AI

71

21.

Dopamine

INDO

72

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED

450

DRUG

DESIGN

T a b l e I I . NMR c o n f o r m a t i o n a l s t u d i e s o f a d r e n e r g i c agents.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

Compound(s)

Solvent

Studied

Ref.

1. E p h e d r i n e Pseudoephedrine ( f r e e bases)

CDCI3

2. E p h e d r i n e Pseudoephedrine ( f r e e bases and HC1 s a l t s )

C C l ^ C ^ CDCl3,DMSO CF3COOH,D20

3. I s o p r o t e r e n o l Epinephrine (TMS e t h e r s )

CCI4

4. Dopamine HC1

D 0

5. Amphetamine ( f r e e base and HC1) Methamphetamine HC1 o-Methoxy-methamphetamine HC1 Benzphetamine HC1

D 0

6. F i v e dimethoxyamphetamines ( f r e e bases)

CDCI3

77

7. E i g h t e e n a r y l - s u b s t i t u t e d amphetamines ( f r e e bases) Nine a r y l - s u b s t i t u t e d amphetamines (HC1 s a l t s )

CDCI3

78

73

75

2

55

2

76

79

8. N - I s o p r o p y l - p - n i t r o p h e n y l e t h y l amine 9. Amphetamine

(free

base)

10. E l e v e n a d r e n e r g i c agents (HC1 s a l t s )

(HO)\^AH Ν Figure 4.

CDCI3

80

D 0

81

2

Ar

Ar

I

74

(HO)^P^H (CHJ

(HO}^P^H Η HI

Newman projections of the major conformations of phenylethylamines

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

21.

GRUNEWALD E T A L .

Analogs

of

Methamphetamine

451

between t h e a r o m a t i c r i n g and t h e n i t r o g e n atom; f u r t h e r , i n compounds b e a r i n g a hydroxy1 group on C-2, I I I w i l l have t h e oxygen atom a n t i p e r i p l a n a r with respect to the nitrogen atom, w h i l e f o r amphetamines, I I I w i l l i n d i c a t e t h a t t h e C - l methyl group i s a l s o gauche w i t h respect t o the aromatic r i n g . Hyne (73) i n v e s t i g a t e d t h e c o n f o r m a t i o n s o f e p h e d r i n e and pseudoephedrine as t h e f r e e bases i n d e u t e r i o c h l o r o f o r m (CDCI3). For ephedrine, the r a t i o o f c o n f o r m a t i o n s I_ ΓΙ and I I I was found t o be 40:40: 20, w h i l e f o r pseudoephedrine t h e r a t i o was 62:30:8. P o r t o g h e s e (74) s u b s e q u e n t l y r e i n v e s t i g a t e d t h e ephedrines. F o r e p h e d r i n e h y d r o c h l o r i d e i n D 0 , he found 90% o f t h e m a t e r i a l t o be i n c o n f o r m a t i o n s which p e r m i t t e d hydrogen bonding between t h e h y d r o x y l and amino groups (-i.e., 90% i n c o n f o r m a t i o n s ,1 and I I ) ; pseudoephedrine h y d r o c h l o r i d e was r e p o r t e d t o have 84% o f t h e extended c o n f o r m a t i o n !E and 16% gauche c o n f o r mers (ΓΙ and I I I ) . These r e s u l t s a r e a c c o u n t e d f o r by two f a c t o r s . F i r s t , hydrogen bonding i n t e r a c t i o n s f a v o r c o n f o r m a t i o n s I^ and I_I f o r b o t h e p h e d r i n e and pseudoephedrine. S e c o n d l y , t h e methyl s u b s t i t u e n t α t o t h e n i t r o g e n atom causes conformers 1^ and I I t o be s t e r i c a l l y l e s s f a v o r a b l e i n e p h e d r i n e , w h i l e T t makes I I and I I I l e s s f a v o r a b l e i n pseudoephedrine. A l a r g e number o f s u b s t i t u t e d amphetamines have been s t u d i e d by NMR. These r e s u l t s a r e summarized i n T a b l e I I I . I n a l l c a s e s , t h e extended c o n f o r m a t i o n (.1) predominated, making up 47-76% o f t h e conformer population. Conformer I_I, i n which t h e m e t h y l group on C - l i s d i r e c t e d away from t h e p h e n y l r i n g , i s a l s o p r e s e n t t o a s i g n i f i c a n t e x t e n t i n a l l c a s e s , making up 21-45% o f t h e sample. C o n f o r m a t i o n I I I , i n which the a r o m a t i c r i n g has gauche i n t e r a c t i o n s w i t h b o t h the m e t h y l group and t h e n i t r o g e n atom, makes up t h e r e m a i n i n g 0-12%. R e s u l t s f o r a v a r i e t y o f o t h e r a d r e n e r g i c agents have been c o m p i l e d i n T a b l e IV. As was t h e case f o r the amphetamines, t h e extended c o n f o r m a t i o n i s by f a r t h e predominant one, w i t h conformer ICI making a sub­ s t a n t i a l c o n t r i b u t i o n i n compounds b e a r i n g a h y d r o x y l group on C-2. The n o t a b l e e x c e p t i o n i s dopamine h y d r o ­ c h l o r i d e , i n which 43% o f t h e extended c o n f o r m a t i o n and 57% o f t h e gauche c o n f o r m a t i o n were o b s e r v e d . In g e n e r a l , NMR experiments have been i n agreement with molecular o r b i t a l c a l c u l a t i o n s . Both extended and gauche conformers a r e u s u a l l y p r e s e n t t o a s i g n i f i c a n t e x t e n t , w i t h t h e extended conformer p r e d o m i n a t i n g . Again, the evidence a v a i l a b l e i s not s u f f i c i e n t t o

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

f

2

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

/

/

2

2

2

2

3

3

3

3

3

3

2

3

2

2

3

3

HC1 HC1 HC1 HC1 HC1 HC1 HC1 fb

2

2,3-(OCH ) 2,4-(OCH ) 2,5-(OCH ) 3,4-(OCH ) 3,5-(OCH ) 2, 3,4-(OCH )3 3 4 5-(OCH )3

3

11. 12. 13. 14. 15. 16. 17. 18.

/

3

3

CH CH3 CH3, CH2C6H5 fb fb fb fb fb

3

fb HC1 HC1 HC1 HC1

Salt

2,3-(OCH )2 2,4-(OCH ) 2 5-(OCH3)2 3,4-(OCH ) 3,5-(OCH )

2-OCH

N-Alkyl

6. 7. 8. 9. 10.

1. 2. 3. 4. 5.

Aromatic Substitution a

CDCI3 CDCI3 CDCI3 CDCI3 CDCI3 CDCI3 CDCI3 CDCI3

CDCI3 CDCI3 CDCI3 CDCI3 CDCI3

2

2

D2O D2O D 0 D2O D 0

Solvent

68 66 65 76 75 65 72 72

67 62 64 64 65

50 50 55 47 64

32 34 35 23 25 35 28 28

21 26 24 25 23

39 45 39 36 35

78 78 78 78 78 78 78 80

77 77 77 77 77 12 12 12 11 12 0 0 0 1 0 0 0 0

76 76 76 76 76

Reference

11 5 6 17 1

Ratio of conformers^ I : II : III

T a b l e I I I . Amphetamine conformer d i s t r i b u t i o n s as d e t e r m i n e d by N.MR. (a) f b = f r e e base. (b) See F i g u r e 4 and t h e t e x t f o r c o n v e n t i o n s used i n s p e c i f y i n g conformations,

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979. b

0

0

3 9 4 21

10 0 f

16

7 9 — 79 — 72

81 81 96

2

D 0 2

D 0 2

D 0 2

D 0 2

D2O D 0 2

D 0 2

D 0

HC1 HC1 HC1 HC1 HC1 HC1 HC1 HC1

8. P h e n y l e t h a n o l a m i n e

9. P h e n y l e p h r i n e

10. S y n e p h r i n e 11. N,N-Dimethyl-o-bromophenylethanolamine

12. N o r e p h e d r i n e

13. M e t a r a m i n o l

14. B u t a n e p h r i n e

15. P h e n y l e t h y l a m i n e

56

6

10 84

D 0

HC1

7. I s o p r o t e r e n o l

2

6

11 83

2

f

28 e

21

6

17

77

D 0

HC1

6. E p i n e p h r i n e

f

10

14

76

D2O

HC1

2

44

57

43

D 0

81

81

81

81

81

81

81

81

81

81

81

79

55 d

HC1

75 d

30

70

CCI4

fb

75

d

50

50

CCI4

fb

5. N o r e p i n e p h r i n e

4. N-Isopropyl-£-nitrophenylethylamine

3. Dopamine

2. E p i n e p h r i n e

1. I s o p r o t e r e n o l

T a b l e IV. NMR c o n f o r m a t i o n a l a n a l y s i s o f some p h e n y l e t h y l a m i n e s . (a) f b = f r e e base. (b) See F i g u r e 4 and t h e t e x t f o r c o n v e n t i o n s used i n s p e c i f y i n g c o n f o r m a t i o n . (c) Determined as t h e TMS e t h e r , (d) Sum o f conformers I I and I I I . (e) I I and I l l are e q u i v a l e n t ; sum o f I I and I I I . (f) Sum o f c o n f o r m e r s I_ and I I . Ratio of conformers Ref. I : II : III Compound Salta Solvent

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

i'

1

>»

•

6

Î

0 w

to

COMPUTER-ASSISTED DRUG DESIGN

454

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

a s s e s s which c o n f o r m a t i o n

is biologically

active.

C o n f o r m a t i o n a l l y - R e s t r i c t e d Analogs. In p r e p a r i n g c o n f o r m a t i o n a l l y - r e s t r i c t e d analogs of a b i o l o g i c a l l y a c t i v e s u b s t a n c e , the e s s e n t i a l s t r u c t u r a l f e a t u r e s o f the a g o n i s t a r e b u i l t i n t o a m o l e c u l a r framework which has l i m i t e d c o n f o r m a t i o n a l m o b i l i t y . With t h i s approach i t i s no l o n g e r n e c e s s a r y t o assume t h a t a p r e d o m i n a t i n g c o n f o r m a t i o n i s a c t i v e , s i n c e the conf o r m a t i o n o f the message m o l e c u l e i s r e s t r i c t e d . When a c o n f o r m a t i o n a l l y - r e s t r i c t e d a n a l o g e x h i b i t s an a c t i v i t y , the c o n f o r m a t i o n a l possibilités r e s p o n s i b l e f o r t h a t a c t i v i t y are w e l l d e f i n e d . Unfortunately, the c o n v e r s e i s not t r u e — when such a n a l o g s a r e i n a c t i v e , t h e r e may be a number o f r e a s o n s o t h e r than i n c o r r e c t conformation. The e x t r a atoms n e c e s s a r y t o make the m o l e c u l e l e s s f l e x i b l e may s t e r i c a l l y i n t e r f e r e w i t h the d r u g - r e c e p t o r r e c o g n i t i o n p r o c e s s . In a d d i t i o n , the e x t r a atoms may a l t e r a b s o r p t i o n , t i s s u e d i s t r i b u t i o n , m e t a b o l i s m and o t h e r c e l l u l a r p r o c e s s e s . The i d e a l c o n f o r m a t i o n a l l y - r e s t r i c t e d a n a l o g s h o u l d p r o v i d e w e l l - d e f i n e d and u n d i s t o r t e d geometry w i t h as few e x t r a atoms as p o s s i b l e . Although a p l e t h o r a of r i g i d and s e m i - r i g i d a n a l o g s o f a d r e n e r g i c agents has appeared i n r e c e n t y e a r s , few have approached t h i s i d e a l ; most have shown l i t t l e o r no b i o l o g i c a l a c t i v i t y e x c e p t a t h i g h c o n c e n t r a t i o n s , and few show pronounced c o n f o r m a t i o n a l s e l e c t i v i t y . Comparisons a r e o f t e n d i f f i c u l t because t h e p h a r m a c o l o g i c a l t e s t i n g performed on t h e s e compounds ranges from s i m p l i s t i c to h i g h l y s o p h i s t i c a t e d . Some compounds would be e x p e c t e d t o show d i r e c t a c t i v i t y ( r e c e p t o r a c t i v a t i o n ) , some i n d i r e c t a c t i v i t y ( r e l e a s e o f n e u r o t r a n s m i t t e r ) , and some might have b o t h k i n d s o f a c t i v i t y . Table V i s a c o m p i l a t i o n o f t h e s e r i n g systems and t h e i r a p p l i cations. A d e t a i l e d r e v i e w i s beyond the scope o f t h i s d i s c u s s i o n , but some comments on the a n a l o g s o f amphetamine a r e p e r t i n e n t . Smissman and coworkers p r e p a r e d a l a r g e number o f t r a n s - d e c a l i n compounds (82-90). The t r a n s - d e c a l i n system i s r e a s o n a b l y r i g i d and may be e x p e c t e d t o p r o v i d e n e a r l y i d e a l d i h e d r a l a n g l e s ; however, the v e r y l a r g e number o f e x t r a atoms makes t h e s e compounds h i g h l y l i p o p h i l i c and c r e a t e s a g r e a t d e a l o f s t e r i c b u l k . The d e c a l i n amphetamine a n a l o g s ( s k e l e t o n 1 i n T a b l e V) were t e s t e d f o r t h e i r e f f e c t on motor a c t i v i t y (06), s i n c e amphetamine i t s e l f i s known t o i n c r e a s e motor activity. P a r a d o x i c a l l y , a l l f o u r compounds d e c r e a s e d motor a c t i v i t y . In a d d i t i o n , the extended conformer caused l a c h r y m a t i o n . L a t e r s t u d i e s (87,88,89) on

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

GRUNEWALD E T A L .

Analogs

of

Methamphetamine

455

T a b l e V. R i n g systems w h i c h have been u t l i z e d i n p r e p a r i n g c o n f o r m a t i o n a l l y - r e s t r i c t e d analogs of adrenergic agents.

S t r u c t u r a l Skeleton

Analogs

Number o f o f ; e x t r a atoms

Ref.

Ar

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

, . Norephedrine ( On ; Anphetamine r*NHR Dopamine trans-decalin Norepinephrine

7-8

8290

Ph OH

Phenylethanol- 7 amine

91

Norephedrine Amphetamine

92 93

Amphetamine

94

•Mi'

trans-decahvdrnquinoline f

octahydrophenanthrene

'h NHR cyclohexane

HO. Norephedrine Norepinephrine

2-3

95, 96, 97

N-Isopropylnorephedrine

7

98

benzocycloheptene

-(CH )g. 2

[10]-paracyclophane

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED

456

Table V

(cont'd.)

Ephedrine Isoproterenol

(0H)

DRUG DESIGN

I

2

1-2

99

NHR

R' chromane

8.

OH

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

100, 101

N-Methyldopamine

HO

NH

octahydrobenzo[f1quinoline

9-

(OH)

OCX 2

NHR £ t 2-aminotetralin R ^

102119

Phenylethylamine Dopamine Norepinephrine Epinephrine

NH

11.

Norephedrine Dopamine Norepinephrine Epinephrine

1

106 120127

tetrahydroisoquinoline R'

(OH),

NHR

Norephedrine Amphetamine Dopamine

103, 105, 123, 128130

2 - aminoindane Ph

12.

Amphetamine

NH

0

2

cyclopropane

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

129, 131133

21.

Analogs

GRUNEWALD E T A L .

Table V

Hi

(OH) Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

lk.

457

Methamphetamine

(cont'd.)

13.

NH

of

Norephedrine Amphetamine Dopamine Metaraminol

1-2

130, 132, 134, 135

Ephedrine

1

136

2

cyclobutane Ph / HN

~"Ύ\ u

OH R azetidine

Phenylethanolamine

15. NHR

Amphetamine Methamphet­ amine

137140

Amphetamine Methamphet-

130, 141144

benzonorbornene

16. NHR

a

m

i

n

e

b e n z o b i c y c l o [ 2 . 2 .2]]octene

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

458

DRUG DESIGN

i n h i b i t i o n o f dopamine uptake i n t o s t r i a t a l t i s s u e showed t h a t a gauche conformer (a-amino, e-phenyl) was c o n s i d e r a b l y more p o t e n t than t h e o t h e r t h r e e i s o m e r s . B l o c k a d e o f t h e uptake o f b i o g e n i c amines i n t o p l a t e l e t s by t h e f o u r amphetamine conformers showed l i t t l e s e l e c t i v i t y (the l e a s t p o t e n t isomer b e i n g 60% as e f f e c t i v e as t h e most p o t e n t ) . Amphetamine a n a l o g s i n s k e l e t o n 3 (£2,93) showed no amphetamine-like b e h a v i o r a l e f f e c t s and no amphetamine-like hyperthermia i n animals. This skeleton i s r i g i d , but shows some d i s t o r t i o n s from normal bond a n g l e s f o r a n t i p e r i p l a n a r and gauche c o n f o r m a t i o n s . S k e l e t o n s 4, 5, 7-11 13 and 14 have v a r y i n g degrees of c o n f o r m a t i o n a l f l e x i b i l i t y which make any c o n f o r m a t i o n - a c t i v i t y r e l a t i o n s h i p s d i f f i c u l t , i f not impossible, to obtain. S k e l e t o n 6 does n o t mimic any of t h e low-energy c o n f o r m a t i o n s o f t h e p h e n y l e t h y l amine s k e l e t o n . A l t h o u g h s k e l e t o n 12 has t h e fewest p o s s i b l e number o f e x t r a atoms (one e x t r a f o r a p h e n y l e t h y l a m i n e and none f o r an amphetamine) t h e bond a n g l e s a r e so d i s t o r t e d t h a t an extended c o n f o r m a t i o n cannot be a c h i e v e d by t h e t r a n s - s u b s t i t u t e d c y c l o p r o p y l system and a gauche conformer cannot be approximated (the c i s - i s o m e r i s a c t u a l l y an e c l i p s e d c o n f o r m e r ) . f

Choice of a Conformationally-Defined Analog In our s e a r c h f o r t h e most s u i t a b l e system f o r the s t u d y o f sympathomimetic amines, we chose i n i t i a l l y t o l o o k a t a system w i t h t h e minimum o f s y n t h e t i c problems i n o b t a i n i n g s u i t a b l e q u a n t i t i e s f o r i n i t i a l pharmacol o g i c a l evaluation. To t h i s end we chose t o l o o k a t amphetamine a n a l o g s , w i t h the u l t i m a t e aim o f a d d i n g t h e 3 - h y d r o x y l and c a t e c h o l h y d r o x y l s t o produce t h e c a t e c h o l a m i n e s . We f e l t t h a t i t was e s s e n t i a l t h a t the system chosen have a minimum number o f " e x t r a " atoms n o t p r e s e n t i n amphetamine (or i t s N-methyl d e r i v a t i v e , methamphetamine). I t was a l s o n e c e s s a r y t h a t the system n o t be h i g h l y s t r a i n e d and t h a t the bond a n g l e s and bond l e n g t h s found i n the low-energy c o n f o r m a t i o n s o f amphetamine be v e r y c l o s e l y a p p r o x i mated i n t h e c o n f o r m a t i o n a l l y - d e f i n e d model. I t was d e s i r e d t h a t any system chosen would show s i m i l a r p h y s i c a l p r o p e r t i e s t o t h o s e o f amphetamine — lipop h i l i c i t y ( p a r t i t i o n c o e f f i c i e n t ) , pKa and charge distribution in particular. Examination of these p o i n t s suggested s k e l e t o n s 15 and 16 o f T a b l e V. S i n c e the b e n z o b i c y c l o [ 2 . 2 . 1 ] heptene a n a l o g s ( s k e l e t o n 15) a r e c o n s i d e r a b l y more s t r a i n e d than t h e b e n z o b i c y c l o [ 2 . 2 . 2 ] o c t e n e ( s k e l e t o n

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

21.

GRUNEWALD E T A L .

Analogs

of

Methamphetamine

459

16), t h e l a t t e r was chosen f o r o u r i n i t i a l s t u d y . However, d e r i v a t i v e s o f s k e l e t o n 15 and i t s oxob r i d g e d a n a l o g , were a l s o p l a n n e d (see F i g u r e 7 ) . F i g u r e s 5 and 6 show t h e r e l a t i o n s h i p o f t h e methamphetamine o r amphetamine a n a l o g s i n s k e l e t o n 16 t o amphetamine and methamphetamine. The b e n z o b i c y c l o [ 2 . 2 . 2 ] o c t e n e system has o n l y t h r e e " e x t r a " atoms and thus appeared t o have a number o f advantages o v e r t h e o t h e r systems i n T a b l e V and F i g u r e 7. F i r s t , t h e two low-energy c o n f o r m a t i o n s o f the p h e n y l e t h y l a m i n e s c a n be c l e a r l y f i x e d (the systems a r e almost c o m p l e t e l y r i g i d , i n c o n t r a s t t o t h e more e x t e n s i v e l y - s t u d i e d systems l i k e s k e l e t o n s 9 and 13 o f Table V). Second, m o l e c u l a r models show t h e r e i s minimal d i s t o r t i o n i n bond a n g l e s o r bond l e n g t h s from t h o s e i n t h e m o b i l e system, amphetamine. T h i s i s n o t so f o r systems I I I - V I I I o f F i g u r e 7. T h i r d , a r e l a t i v e l y s i m p l e s y n t h e t i c p r o c e d u r e would a f f o r d b o t h the endo- and exp-isomers o f amphetamine (NH-N and NHX) o r methamphetamine (NM-N and NM-X) so t h e system c o u l d be e v a l u a t e d by x - r a y c r y s t a l l o g r a p h y t o d e t e r mine t h e p r e c i s e bond a n g l e s and bond l e n g t h s i n comparison t o t h o s e o f t h e m o b i l e (amphetamine) system. U s i n g t h e atomic c o o r d i n a t e s o f t h e x - r a y s t u d y , m o l e c u l a r o r b i t a l c a l c u l a t i o n s c o u l d be c a r r i e d o u t t o compare t h e r i g i d system w i t h t h e m o b i l e system (/i.e., charge d i s t r i b u t i o n s ) . And, most i m p o r t a n t l y , i t c o u l d be e v a l u a t e d p h a r m a c o l o g i c a l l y i n comparison w i t h t h e m o b i l e drug t o see i f c o n f o r m a t i o n a l d i f f e r e n c e s i n a c t i v i t y were p r e s e n t . Any d i f f e r e n c e s c o u l d then be i n t e r p r e t e d i n terms o f p r e c i s e c o n f o r m a t i o n a l arguments. To date t h e b e n z o b i c y c l o [ 2 . 2 . 2 ] o c t e n e system has l i v e d up t o i t s e x p e c t a t i o n s . I n t h e r e m a i n i n g p a r t o f t h i s d i s c u s s i o n we w i l l a d d r e s s the above p o i n t s . E v a l u a t i o n o f Some B i c y c l i c Systems as Conformationally-Defined Phenylethylamines. X-Ray Crystallography. Perhaps t h e u l t i m a t e t e s t o f t h e s u i t a b i l i t y o f a chemical s t r u c t u r e f o r preparing c o n f o r m a t i o n a l l y - d e f i n e d a n a l o g s would be t h e i r a b i l i t y t o produce b i o l o g i c a l e f f e c t s i d e n t i c a l t o t h o s e o f t h e p a r e n t compound. S i n c e t h i s i d e a l i s r a r e l y a c h i e v e d , and s i n c e a "wrong" conformer s h o u l d be i n a c t i v e , i t i s u s e f u l t o have o t h e r c r i t e r i a w i t h which t o e v a l u a t e t h e s e systems. The b i c y c l i c molec u l e s t o be examined i n t h e p r e s e n t s t u d y a r e compounds I - V I I I ( F i g u r e 7 ) , b e n z o b i c y c l o [ 2 . 2 . 2 ] o c t e n e s , benzob i c y c l o [2.2.1]heptenes, and 1 , 2 , 3 , 4 - t e t r a h y d r o - l , 4 epoxynaphthalenes. A number o f s t r u c t u r a l parameters

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

460

Ο

NH

2

r CH ,HMi

3

'gauche' amphetamine

'anti' amphetamine

o

NHR

Η

exo-analog NH-X (R = H) NM-X (R=CH ) 3

NHR endo-analog NH-N

(R=H)

NM-N (R=CH ) 3

Figure 5. Relationship of the exo- and endo-2-amino- and 2-methylaminobenzobicyclo[2.2.2]octenes to the two low energy conformations of amphetamine and methamphetamine. The abbreviations shown for the conformational^ defined analogs are used throughout the text.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

GRUNEWALD E T A L .

Analogs

of

Methamphetamine

461

€13

Figure 6. ORTEP drawings of (a) amphetamine (146) drawn in the same perspective as that for (b) 2-methylaminobenzobicyclo[ 2.2.2 Joctene ( exo-isomer NM-X) and (c) endo-isomer NM-N (145).

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

462

ο 0

VII(OH-X) Figure 7.

"

1

Γ1

'2

VIII(OH-N)

Conformationally defined analogs of phenylethylamines (see text)

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

21.

GRUNEWALD E T A L .

Analogs of Methamphetamine

463

( d i h e d r a l a n g l e s , bond a n g l e s and i n t e r a t o m i c d i s t a n c e s ) can be determined f o r t h e s e b i c y c l i c p h e n y l e t h y l a m i n e a n a l o g s s i n c e t h e carbon s k e l e t o n s o f t h e s e compounds have almost no f l e x i b i l i t y . These s t r u c t u r a l parameters can be compared w i t h t h e c o r r e s p o n d i n g v a l u e s d e r i v e d from x - r a y s t r u c t u r e d e t e r m i n a t i o n s and molecular o r b i t a l c a l c u l a t i o n s of phenylethylamines. The d i h e d r a l a n g l e s τ.^, T , ' , T and τ ~ ( i l l u s t r a t e d on s t r u c t u r e s I - I V o f F i g u r e 7j c o r r e s p o n d t o t h o s e i n F i g u r e 2. The s i g n i f i c a n t bond a n g l e s ( 9 w 0 ^ and θ ) a r e d e f i n e d i n s t r u c t u r e s V-VII o f F i g u r e 7. I n t e r a t o m i c d i s t a n c e s between f u n c t i o n a l groups p r o v i d e a measure o f how a c c u r a t e l y t h e r i g i d s t r u c ­ t u r e s approximate t h e s p a t i a l placement o f t h e s e groups as o b s e r v e d i n c o n f o r m a t i o n a l l y - m o b i l e p h e n y l ­ ethylamines. The f u n c t i o n a l groups o f i n t e r e s t (shown on s t r u c t u r e V I I I ) i n c l u d e t h e n i t r o g e n atom, t h e oxygen atom on C-2, t h e a r o m a t i c oxygen s u b s t i t u e n t s and t h e a r o m a t i c r i n g . Determination o f these d i s t a n c e s and a n g l e s was based on x - r a y s t r u c t u r e d e t e r m i n a t i o n s o f compounds h a v i n g t h e b e n z o b i c y c l o [2.2.2]octene (145) o r b e n z o b i c y c l o [ 2 . 2 . 1 ] h e p t e n e (147) r i n g systems. Where n e c e s s a r y , e x t r a atoms were added, u s i n g s t a n d a r d bond l e n g t h s and a n g l e s (44). These c a l c u l a t i o n s were c a r r i e d o u t w i t h t h e computer programs QCLM/ICOORD and QCLM/COORD (made a v a i l a b l e t o us by t h e Quantum C h e m i s t r y Group a t t h e U n i v e r s i t y o f Kansas) which c a l c u l a t e bond l e n g t h s , bond a n g l e s , d i h e d r a l a n g l e s and i n t e r a t o m i c d i s t a n c e s from atomic coordinates. The p o s i t i o n o f t h e a r o m a t i c r i n g was r e p r e s e n t e d by t h e c e n t e r o f t h e r i n g (CR), which was d e t e r m i n e d by a v e r a g i n g t h e c o o r d i n a t e s o f t h e s i x carbon atoms which make up t h e r i n g . 2

f

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

2

The x - r a y s t r u c t u r e d e t e r m i n a t i o n s o f exo- and endo-2-methylamino-1,2,3,4-tetrahydro-l,4-ethanonapht h a l e n e h y d r o c h l o r i d e s (145) s e r v e d as t h e b a s i s f o r c a l c u l a t i o n s o f t h e b e n z o b i c y c l o [ 2 . 2 . 2 ] o c t e n e compounds (NM-X and NM-N). The b e n z o b i c y c l o [ 2 . 2 . 1 ] h e p t e n e and 1 , 2 , 3 , 4 - t e t r a ­ h y d r o - l ,4-epoxynaphthalene systems were c o n s t r u c t e d from t h e c o o r d i n a t e d a t a f o r b e n z o b i c y c l o [ 2 . 2 . 1 ] h e p t e n e s y n - and - a n t i - b r o m o b e n z e n e s u l f o n a t e s (147). Positions f o r t h e exo and endo amino groups were s e l e c t e d by u s i n g a s t a n d a r d C-N bond l e n g t h w i t h t h e bond a n g l e s and d i h e d r a l a n g l e s c a l c u l a t e d from a c r y s t a l l o g r a p h i c study o f 2-exo-aminonorbornane-2-carboxylic a c i d (148). The d i h e d r a l a n g l e τ , d e s c r i b e s t h e r o t a t i o n o f the a r o m a t i c r i n g w i t h r e s p e c t t o t h e e t h y l a m i n e s i d e c h a i n (see F i g u r e s 2 and 7 ) . Compared w i t h v a l u e s found i n x - r a y s t u d i e s and m o l e c u l a r o r b i t a l c a l c u l a -

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED

464

DRUG DESIGN

t i o n s , t h e benzobicyclo[2.2·1] compounds p r o v i d e a b e t t e r a p p r o x i m a t i o n o f t h i s a n g l e than do the benzo­ b i c y c l o [2.2.2] compounds. T h i s i s r e p r e s e n t e d g r a p h i c a l l y i n F i g u r e 8. V a l u e s o f τ, o b s e r v e d i n x - r a y s t u d i e s (see above) a r e d e p i c t e d a l o n g w i t h the r e s u l t p r e d i c t e d by m o l e c u l a r o r b i t a l (see T a b l e VII) c a l c u l a t i o n s (90°). Compounds I I I - V I I I form an a n g l e o f 6 9 ° , w h i l e t h e b i c y c l o [ 2 . 2 . 2 ] compounds form a 60° d i h e d r a l angle. The comparison of τ v a l u e s may be d i v i d e d i n t o two groups: t h o s e f o r extended conformers ( τ = 180°) and t h o s e f o r gauche conformers ( τ = 6 0 ° ) . Both groups a r e d e p i c t e d i n F i g u r e 9. The a n a l o g s h a v i n g an extended c o n f o r m a t i o n a l l g i v e τ v a l u e s w e l l w i t h i n t h e range o f o b s e r v e d v a l u e s f o r extended phenylethylamines: the exo-benzobicyclo[2.2.2]octene isomer g i v e s a n e a r l y i d e a l τ d i h e d r a l a n g l e (179°); the exo-[2.2.1] compounds a r e n e a r l y as good (176°) , w h i l e the a n t i - [ 2 . 2 . 1 ] compound forms an a n g l e o f 168°. The gauche conformers a r e more d i f f i c u l t t o e v a l u a t e , s i n c e observed τ values are a v a i l a b l e f o r only three gauche p h e n y l e t h y l a m i n e s . A l l four conformationallyd e f i n e d s t r u c t u r e s a r e w i t h i n 10° o f the o b s e r v e d and c a l c u l a t e d v a l u e s , as i l l u s t r a t e d i n F i g u r e 9. The endo- [2.2.1] s t r u c t u r e ( τ = 59°) most n e a r l y approximates t h e p r e d i c t e d v a l u e o f 60°. The endo[2.2.2] and syn-[2.2.1] compounds form a n g l e s o f 69° and 70°, r e s p e c t i v e l y . B u i l d i n g the C-2 oxygen atom i n t o t h e b i c y c l o [2.2.1] r i n g system s e r i o u s l y d i s t o r t s τ ~ , the O-C-C-N d i h e d r a l a n g l e . As shown i n F i g u r e 10, t h e benzo­ b i c y c l o [2 . 2 . 2 ] o c t e n e s p r o v i d e e x c e l l e n t v a l u e s f o r ~ (endo, 59°; exo, 56°), but V I I forms an 83° a n g l e . The endo isomer V I I I , which approximates an a n t i p e r i p l a n a r arrangement o f t h e oxygen and n i t r o g e n atoms, forms an a n g l e o f 160°, compared t o a p r e d i c t e d a n g l e o f 180°. The bond a n g l e s θ , , Θ , and θ p r o v i d e an i n d i c a t i o n o f t h e amount or r i n g s t r a i n i n the b i c y c l i c ring structures. I d e a l l y , Θ, and θ, s h o u l d be 120°; i n t h e [2.2.2] r i n g system, t h i s i s d i s t o r t e d by about 7 ° , and i n t h e [2.2.1] s t r u c t u r e s i t i s n e a r l y t w i c e as d i s t o r t e d (by about 1 2 ° ) . The C1 -C2-C1 a n g l e ( θ ) i s w i t h i n t h r e e degrees o f the i d e a l t e t r a h e d r a l a n g l e (109°) f o r compounds I , I I , I I I , IV, V I I and V I I I . ^ _y ~ * a n t i - [2.2.1] s t r u c t u r e s , however, have θ v a l u e s o f 100° and 96°, r e s p e c t i v e l y . The s p a t i a l arrangement o f f u n c t i o n a l groups would appear t o be p a r t i c u l a r l y i m p o r t a n t i n o r d e r f o r conf o r m a t i o n a l l y - r e s t r i c t e d analogs to e x h i b i t b i o l o g i c a l 2

2

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

2

2

2

2

2

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Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

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In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

7.66

7.25

6.03

7.66

6.17

7.79

5.03

4.74

3.69

5.03

3.85

5.10

IV

V

VI

VII

VIII

XI

X i ii iii iv

3.89

6.27

6.17

3.85

III

5.18 5.17 5.21 5.12

6.27

3.89

II

IX

7.68

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5.07

A

(cont'd.)

I

a

Compound

TABLE VI

4.33 4.33

5.80 4.32 5.80 4.32

5.83 5.83

3.31 3.31 3.72

3.09 3.82 2.85

3.84 5.09 5.52 4.53 5.09 3.84

5.49 5.51 7.15 6.34 7. 23 5.47 5.94 4.65 7.15 6.34 5.49 5.51

5.25 5.93

(a) R e f e r e n c e 38; (b) r e f e r e n c e 146. The a u t h o r s o f t h i s r e f e r e n c e r e p o r t τι v a l u e s o f 7 2 0 , 7 7 0 , 7 0 ° and 83° f o r i - i v , r e s p e c t i v e l y ; (c) r e f e r e n c e 42. The a u t h o r s r e p o r t a τ value of 56°. 2

2.39

5.08 6.02

6.28

3.78

2.87

3.95

5.76 5.54

6.85

2.39

5.08 6.02

6.28

3.78

G

3.01

F

3

5.33

Ε

Distances

6.37 7.38

D

Interatomic

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

470

C O M P U T E R - A S S I S T E D D R U G DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

N u m b e r of observations

H

ο

Figure 12. Comparison of the distances from the nitrogen to the para-oxygen in some conformationally defined analogs of phenylethylamines with those found from x-ray crystallographic studies reported for phenylethylamines (see text)

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch021

21.

GRUNEWALD E T A L .

Analogs

of

Methamphetamine

471

e t h y l a m i n e s which have such a c o n f o r m a t i o n i n the c r y s t a l s t r u c t u r e , so comparisons a r e not p o s s i b l e i n this instance. The o b s e r v e d i n t e r a t o m i c d i s t a n c e from t h e c e n t e r of the a r o m a t i c r i n g t o t h e C2-oxygen atom (CR t o C2-0£ ranges from 3.53 t o 3.76 Â, w i t h a mean v a l u e o f 3.68 A. The b e n z o b i c y c l o [ 2 . 2 . 2 ] o c t e n e system g i v e s a r e a s o n a b l y good CR t o C2-0 d i s t a n c e (3.78 A ) . As might be e x p e c t e d , compounds V I I and V I I I , i n which t h e oxygen atom i s b u i l t i n t o a somewhat s t r a i n e d s t r u c t u r e , p r o v i d e a much l e s s a c c u r a t e CR t o C2-0 d i s t a n c e , 3.31 Â. In g e n e r a l , t h e b e n z o b i c y c l o [ 2 . 2 . 2 ] o c t e n e r i n g system a f f o r d s t h e b e s t model o f gauche and extended phenylethylamine conformers. I t s main drawback would appear t o be t h e s l i g h t l y low v a l u e o f τ·^. The exo and e n d o - b e n z o b i c y c l o [ 2 . 2 . 1 ] h e p t e n e s ( s t r u c t u r e s I I I and IV)and t h e 1,2,3,4-tetrahydro-l,4-epoxynaphthalenes (VII and V I I I ) p r o v i d e m o d e r a t e l y good a p p r o x i m a t i o n s of p h e n y l e t h y l a m i n e c o n f o r m a t i o n s , a l t h o u g h t h e p l a c e ­ ment o f t h e C2-oxygen atom i s somewhat d i s t o r t e d i n s t r u c t u r e s V I I and V I I I . The s y n - and a n t i - b e n z o b i c y c l o [ 2 . 2 . 1 ] h e p t e n e s (V and VI) seem t o be t h e l e a s t s u i t a b l e o f the s t r u c t u r e s s t u d i e d ; d i h e d r a l a n g l e s , bond a n g l e s and i n t e r a t o m i c d i s t a n c e s d i f f e r s u b s t a n ­ t i a l l y from p r e d i c t e d and o b s e r v e d v a l u e s . A l l t h i n g s c o n s i d e r e d , the b e s t systems appear t o be I and I I (NM-X and NM-N f o r methamphetamine a n a l o g s ) . E v a l u a t i o n o f Some B i c y c l i c Systems as Conformationally-Defined Phenylethylamines. CNDO/2 C a l c u l a t i o n s on Amphetamines. Quantum m e c h a n i c a l s t u d i e s on p h e n y l e t h y l a m i n e and amphetamine have been c a r r i e d o u t p r e v i o u s l y by Pullman and coworkers (59,67) u s i n g b o t h t h e s e m i - e m p i r i c a l PCILO and an ab i n i t i o method, and by H a l l and coworkers (71) u s i n g an ab i n i t i o method. The r e s u l t s o f t h e s e two groups were quite simi1ar. Our aim b e i n g t o i n v e s t i g a t e b o t h t h e energy d i f f e r e n c e s and t h e charge d i s t r i b u t i o n s o f a v a r i e t y of p h e n y l e t h y l a m i n e s , we chose the CNDO/2 method o f P o p l e kown In VIQUKZ 13, not TlguKo, 2 ) : 5

z

and τ 7 ( C - N C -C ) ? (The uèual c o n v e n t i o n f o r t o r s i o n a n g l e s was f o l l o w e d : t h u s , τ, i s t h e a n g l e between t h e p l a n e s t h r o u g h C.C C ana C C C . The a n g l e i s p o s i t i v e f o r c l o c k w i s e r o t a t i o n s about 6 ~ 7 l o o k i n g from C t o C-). When Ν i s u n s u b s t i t u t e d , thé energy i s n e a r l y indépendent o f τ- (71.) / and so i t i s ignored. When " 2 5 ( 9 1 3 ) , τ - must be chosen with care, but reasonable values f o r are readily found from an e x a m i n a t i o n o f m o l e c u l a r models, and were v e r i f i e d by a m i n i m a l number o f t r i a l c a l c u l a t i o n s . Energy s u r f a c e s f o r amphetamine and N-ethylamphetamine have been p l o t t e d i n t h e c o n v e n t i o n a l way as f u n c t i o n s o f τ, and τ ( F i g u r e s 14 and 15). I n a d d i t i o n , t h e v a r i a t i o n o f t h e energy s u r f a c e o f Nethylamphetamine as a f u n c t i o n o f τ and τ i s presented (Figure 16). Because o f t h e r i n g symmetry, t h e maps o f amphet­ amine and N-ethylamphetamine ( F i g u r e s 14 and 15) a r e p e r i o d i c i n T ^ , w i t h p e r i o d 180°. The energy map o f amphetamine i s p r e s e n t e d i n F i g u r e 14. R o t a t i o n s were c a r r i e d o u t about τ, and τ i n a p p r o x i m a t e l y 30° i n c r e m e n t s , p o i n t s b e i n g added t o t h e b a s i c g r i d where i t was thought n e c e s s a r y , p a r t i c u l a r l y i n t h e a r e a 80° 5

)

2

- 0.804 ( c r _ 5 ) 3

> R

2

(n60,r0.92Î,s0.172)

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

514

COMPUTER-ASSISTED DRUG DESIGN

Table IV Buccal Absorption o f an A c i d and a Base a t S i x pH Values and Physicochemical

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch023

Constants Used f o r Eq 9 , 10

propranolol

Log Ρ

PKa

pi

3.33

9.45

5.08 6.02 7.00 7.93 8.94 9.93

-4.37 -3.43 -2.45 -1.52 -0.63 -0.12

Log D

0bsd.

-1.04 -0.10 0.88 1.81 2.70 3.21

-2.19 -1.71 -1.22 -0.79 -0.53 -0.35

-2.01 -1.69 -1.34 -1.02 -0.71 -0.54

-2.22 -1.70 -1.25 -0.90 -0.65 -0.54

-0.46 -0.54 -0.72 -1.07 -1.44 -1.78

-0.19 -0.39 -0.70 -1.05 -1.40 -1.75

-0.40 -0.47 -0.64 -0.93 -1.31 -1.79

H 6 13 (^)^ C

4.0 5.0 6.0 7.0 8.0 9.0 R e f e r e n c e 8.

H


le VI Bacteriostatic Activity

of

litrophenols and Physicochemical

Constants Used f o r Eq 14 Phenol Substitution

Log Ρ

3-N0

2.02

2

4-NO2

2-NH ,4-N0 2

2,5-(N0 ) 2

2

2

Log D

Log 1/MIC 0bsd. Calcd.

8.36

D 6.5 0

2.02

2.59

2.50

1.98

7.16

-0.09

1.89

3.00

3.10

1.07

7.00

-0.12

0.95

2.48

2.49

2.02

5.22

-1.28

0.74

3.46

3.37

pK

a

C

a

2-NH ,4,6-(N0 ) 1.40

4.4

-2.1

-0.70

2.52

2.76

2,4-(N0 )

2

1.52

4.10

-2.40

-0.88

2.96

2.80

2,6-(N0 )

2

1.57

3.71

-2.79

-1.22

2.80

2.78

1.34

0.38

-6.12

-4.78

2.05

2.04

2

2

2

2

2,4,6-(N0 ) 2

a

3

R e f e r e n c e 16

2

''Equation 14.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

b

23.

SCHERRER AND HOWARD

Electronic

Factors

in

519

QSAR

F u j i t a (17) introduced the concept of c o r r e c t i n g the measured c o n c e n t r a t i o n f o r i o n i z a t i o n . His treatment i s e q u i ­ v a l e n t to s u b t r a c t i n g C from the observed l o g 1/C (eq 1 7 ) . D

pH 6.5 (17)

l o g 1/C - C u

n

= 0.896 l o g Ρ - 0.789 pK (3.76) (23.3)

a

+ 7.124

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch023

(n = 8 , r = 0 . 9 9 6 , s = 0 . 2 0 3 , F = 295) Note t h a t Cp i s r e q u i r e d to have a c o e f f i c i e n t of 1. If one c a l c u l a t e s the p r e d i c t e d "log 1/C - Co" values and adds back Cp, the l o g 1/C values obtained are not the same as those c a l c u l a t e d from eq 14; t h e i r c o r r e l a t i o n with observed l o g 1/C i s 0.946. I l i k e n the d i f f e r e n c e to c o r r e c t i n g f o r the i n i t i a l p a r t i t i o n i n g using F u j i t a ' s method, but c o r r e c t i n g f o r a l l sub­ sequent p a r t i t i o n i n g s as well using l o g D. F u j i t a ' s treatment would be d r a s t i c a l l y d i f f e r e n t from an equation t h a t i s q u a d r a t i c i n log D. Binding to M i t o c h o n d r i a l P r o t e i n . The b i n d i n g of phenols to m i t o c h o n d r i a l p r o t e i n (18, 19) a l s o has an e l e c t r o n i c compo­ nent, eq 18. Higher a c i d i t y favors t h i s component, but t h i s f a c t o r i s not as important as the negative i n f l u e n c e due to increased aqueous s o l u b i l i t y . The more a c i d i c a phenol o f a given log P, the l e s s w e l l i t w i l l b i n d . (18)

l o g % bound = 0.235 l o g D - 0.095 pK (12.77) (6.16)

a

+ 1.674

(n = 7, r = 0 . 9 8 8 , s = 0.063, F = 83) I n h i b i t i o n of C h l o r i d e Passage Across Red C e l l Membranes. Phenols i n h i b i t the passage of c h l o r i d e ion across the red eel 1 membrane. Motais e t a l . (15) examined t h i s property f o r some of the same phenols (Table V) as those used f o r uncoupling s t u d i e s by Stockdale & Selwyn. A f a i r c o r r e l a t i o n can be obtained with log D and pK (eq 19). H a l f of these phenols are not a p p r e c i a b l y i o n i z e d under the experimental c o n d i t i o n s . Since many n o n a c i d i c compounds are a l s o a c t i v e , we wondered i f i t r e a l l y mattered f o r the unionized phenols whether the pK was 9 or 10 or 11. Why not use CD as a parameter which w i l l p a r a l l e l the pK f o r i o n i z e d phenols, but w i l l be zero f o r unionized phenols? A s u p e r i o r treatment r e s u l t s when a CQ term i s used, eq 20. Cp i s the l o g ­ arithm of the f r a c t i o n of phenol u n i o n i z e d . The f o l l o w i n g i n t e r ­ p r e t a t i o n i s p o s s i b l e : Cp i s zero f o r unionized phenols ( p K - p H > l ) , so f o r t h e s e , a c t i v i t y i s p r e d i c t e d by the l o g D term. For a given l o g D, i f a phenol i s i o n i z e d under the e x p e r i ­ mental c o n d i t i o n s , i t w i l l have an a d d i t i o n a l c a l c u l a t e d a c t i v i t y increment from the CQ term. A l s o f o r i o n i z e d phenols, f o r a a

a

a

a

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

520

given l o g P, the more a c i d i c the phenol, the more a c t i v e i t w i l l be. This can be s a i d because the c o e f f i c i e n t of the Cp term i s greater than the c o e f f i c i e n t o f l o g D. I t i s p o s s i b l e there are two mechanisms f o r the i n h i b i t i o n of c h l o r i d e ion t r a n s p o r t . By c o n t r a s t , i n no case has the use of a C term improved the c o r r e l a t i o n f o r uncoupling a c t i v i t y . D

(19)

l o g 1/C = 0.547 l o g D - 0.430 pK (4.91)

a

+ 6.393

(5.54)

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch023

(n = 16, r = 0 . 8 4 3 , s = 0 . 4 6 5 , F = 16) (20)

l o g 1/C = 0.915 l o g D - 1.058 Cn + 1.645 (10.05) (10.44) (n = 16, r = 0 . 9 4 7 , s = 0 . 2 7 8 , F = 56)

Uncoupling of O x i d a t i v e Phosphorylation Classes.

by a V a r i e t y o f Chemical

As an a l t e r n a t i v e t e s t of d i s t r i b u t i o n c o e f f i c i e n t s i t i s i n f o r m a t i v e to look a t a s i n g l e b i o l o g i c a l a c t i v i t y , uncoupling o x i d a t i v e p h o s p h o r y l a t i o n , by a v a r i e t y of c l a s s e s of agents. N-Ary1anthrani1ic Acids ( 2 ) . In equations 21 and 22 i t can be seen t h a t the N - a r y l a n t h r a n î l i c a c i d s are s i m i l a r to phenols (eq 12, 13) i n the e f f e c t o f pK on a c t i v i t y . The more a c i d i c the a n t h r a n i l i e a c i d , the more potent i t w i l l be as an uncoupler f o r any given l o g P. In c o n t r a s t , b i n d i n g to bovine serum albumin f o r some o f the same compounds i s s a t i s f i e d by an equat i o n i n l o g D alone (eq 2 3 ) . The pK terms i n eq 21 and 22 may not be s i g n i f i c a n t enough to make anything of the d i f f e r e n c e i n magnitude o f the pK c o e f f i c i e n t s between heart and l i v e r m i t o c h o n d r i a , but t h i s i s a p o t e n t i a l t o o l f o r t h i s type o f comparison. a

a

a

(21)

(heart) l o g 1/C = 0.417 l o g D - 0.864 pK + 7.462 (4.12) ( 2 . 2 4 , 94.4%) a

(n = 1 1 , r = 0 . 8 7 3 , s = 0 . 2 7 5 , F = 12.8) (22)

(liver) l o g 1/C = 0.488 l o g D - 0.572 pK + 5.374 (7.64) ( 2 . 3 0 , 95.6%) a

(n = 13, r = 0 . 9 3 2 , s = 0 . 1 8 9 , F = 33) (23)

( b i n d i n g to BSA) l o g Κ = O - l g O ^ Q g D + 5.373 (n = 8 , r = 0.957, s = 0 . 0 4 1 , F = 66)

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch023

23.

SCHERRER AND HOWARD

Electronic

Factors

in

QSAR

521

a-Aryl-a-cyanocarbonylphenylhydrazones (1). The 47 a-aryl-α-cyanocarbonylphenylhydrazones f o r which measured l o g Ρ values were a v a i l a b l e (9_,10.) were examined by u s , eq 24. The c o r r e l a t i o n c o e f f i c i e n t , 0 . 8 3 , i s lower than f o r the other examples, but c o n s i d e r i n g the d i f f i c u l t y i n g e t t i n g a c o r r e l a t i o n to the 0.92 l e v e l , eq 11 (T4,1J5), i t does not seem too bad. A g a i n , the more a c i d i c the hydrazone, f o r a given l o g P, the more a c t i v e i t w i l l be as an uncoupler. (24)

l o g 1/C = 0.447 l o g D - 0.522 pK (8.63) (8.69)

a

+ 8.036

(n = 4 7 , r = 0.830, s = 0 . 2 5 5 , F = 49) 2 - A r y l - l , 3 - i n d a n e d i o n e s ( 3 ) . At one time a proposed r e l a t i o n s h i p between uncoupling a c t i v i t y and a n t i i n f l a m m a t o r y a c t i v i t y had a f a i r amount o f support. I t was of s p e c i a l i n t e r e s t t h e r e f o r e to see what our approach could do with the data o f van den Berg and a s s o c i a t e s f o r uncoupling (21_) and f o r the i n h i b i t i o n of p r o s t a g l a n d i n synthetase (22J by a s e r i e s o f 2 - a r y l i n d a n e d i o n e s . We omitted o - s u b s t i t u t e d phenyl d e r i v ­ a t i v e s from uncoupling s t u d i e s because o f the u n a v a i l a b i l i t y o f pK v a l u e s . (They are i n a c t i v e i n i n h i b i t i n g PG s y n t h e t a s e . ) van den Berg and a s s o c i a t e s found o - d e r i v a t i v e s to r e q u i r e separate parameters f o r good c o r r e l a t i o n s . They s t a t e t h a t uncoupling a c t i v i t y i s mainly governed by p a r t i t i o n c o e f f i c i e n t . What one can say from eq 25 i s t h a t there i s a s t r o n g e l e c t r o n i c component to the mechanism of a c t i o n of these a g e n t s , but i n c o n t r a s t to the previous examples, t h i s i s not enough to o v e r ­ come the negative e f f e c t s on d i s t r i b u t i o n . a

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

522 (25)

COMPUTER-ASSISTED DRUG DESIGN

l o g 1/C = 0.508 l o g D - 0.308 pK (15.82)

+ 5.348

a

(3.26)

(n = 24, r = 0 . 9 6 7 , s = 0 . 1 6 5 , F = 154) van den Berg et_ a K r e p o r t eq 26 f o r the same 24 d e r i v a t i v e s .

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch023

(26)

l o g 1/C = 0.504 π - 0.347 σ + 3.813

(η = 24, r = 0 . 9 6 8 , s = 0.164) The negative sigma c o e f f i c i e n t i n eq 26 i n d i c a t e s t h a t e l e c t r o n withdrawing groups are unfavorable. But i t i s n ' t c l e a r from t h i s equation t h a t t h i s i s due to an unfavorable e f f e c t on d i s t r i b u t i o n and t h a t the σ component r e l a t i n g to mechanism i s p o s i t i v e ( i . e . a +σ corresponds to a - p K term i n eq 2 5 ) . o r t h o - D e r i v a t i v e s required an E| term. Since ortho s u b s t i t u t i o n a l s o reduces a c i d i t y , the true i n f l u e n c e of s t e r i c f a c t o r s on uncoupling, separated from i n f l u e n c e s on a c i d i t y - d i s t r i b u t i o n , can only be determined by using Ef with l o g D. Comparison of eq 27 f o r the i n h i b i t i o n of p r o s t a g l a n d i n s y n t h e s i s with eq 25 f o r uncoupling allows one to s t a t e t h a t the e f f e c t of i n c r e a s i n g a c i d i t y (lowering pK ) on the two b i o l o g i c a l a c t i v i t i e s i s i n opposite d i r e c t i o n s . For each pK u n i t the a c i d i t y of a 2-arylindanedione i s increased (with the same l o g P ) , the d i f f e r e n c e between the two a c t i v i t i e s w i l l increase 15 f o l d . (Note t h a t i t doesn't matter, f o r t h i s comparison, t h a t the values f o r the two equations were obtained at d i f f e r e n t pH's. The equations should hold f o r any pH not a f f e c t i n g the system i t s e l f . ) a

a

[ I n h i b i t i o n of p r o s t a g l a n d i n synthesis (27)

(1_7) Table

VII.]

l o g 1 / I C ™ = 0.382 l o q D - 1.354 pK + 9.420 (8.58Γ (10.36) a

W

(n = 24, r = 0 . 9 2 0 , s = 0 . 2 2 8 , F = 58) B a c t e r i o s t a t i c A c t i v i t y of Carboxylic Acids These f i n a l examples are included to emphasize one p a r t i c u l a r p o i n t : the importance of v a r y i n g pK i n a s e r i e s to be able to d e t e c t a p o s s i b l e r o l e f o r e l e c t r o n i c e f f e c t s . The b a c t e r i o s t a t i c a c t i v i t y o f α-hydroxy f a t t y a c i d s a t several pH's was reported by Eggerth (23) and analyzed by Hansch and Clayton (24). They reported the f o l l o w i n g c o r r e l a t i o n s ( f o r B. l e p i s e p t i c u s ) : a

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

2

3

5

2

3

5

3

2

3

5

8

5

1 7

2

2

2

2

R e f e r e n c e 21

6

2

2

3,5-Cl 4 - CHo 4-C fl 4-i-Pr 4-t-Bu 4-n-C H 4-C H 4-OCH, 4-CF 4-C1 4-Br

3 - C1

3-CH 3-C H 3-iPr 3-t-Bu 3,5-(CH ) 3,5-(C H ) 3,5-(i-Pr) 3,5-(t-Bu) 3-OCH3 3,5-(0CH ) 3-CF3

Η

3.98 4.09 4.09 4.09 4.14 4.21 4.21 4.21 4.31 3.84 3.70 3.18 3.35 2.73 26 23 23 31 25 96 4.43 3.06 3.59 3.52

^Equation 25

2.90 3.46 3.92 4.43 4.88 4.02 4.94 5.96 6.86 .88 .86 .78 .61 .32 .46 3.92 4.43 4.88 6.93 4.79 2.88 3.78 3.61 3.76

S u b s t i t u t i o n on 2-phenyl Log Ρ 5

R e f e r e n c e 22

-0.62 0.05 0.51 1.02 1.52 0.73 1.65 2.67 3.67 -0.78 -0.94 -0.54 -0.54 -0.45 0.22 0.65 1.16 1.69 3.68 1.25 -0.19 -0.66 -0.30 -0.22

7

"Equation 27

-1.42 -0.75 -0.29 0.22 0.72 -0.07 0.85 1.87 2.87 58 74 ,34 ,34 ,25 ,58 -0.15 0.36 0.89 2.88 0.45 -0.99 -1.46 -1.10 -1.02

8 > 3

3.74 4.01 4.42 4.69 4.95 4.42 5.06 5.41 5.61 3.62 3.38 3.99 4.02 4.31 4.10 4.53 4.87 5.03 5.66 4.98 3.75 4.11 4.20 4.31

a

{

3.81 4.12 4.35 4.61 4.85 4.42 4.89 5.41 5.89 3.77 3.73 4.10 4.04 4.28 4.15 4.38 4.64 4.88 5.91 4.76 3.89 4.07 4.09 4.15

22 49 52 83 09 42 3.80 4.17 4.95 .50 .78 .47 .16 .19 .60 3.84 3.84 3.89 4.68 4.73 37 94 38 40

3.49 60 77 96 09 69 04 43 68 62 74 60 37 5.25 43 63 83 92 76 23 3.04 4.72 4.14 4.26

Table VII Uncoupling A c t i v i t y I n h i b i t i o n of P r o s t a g l a n d i n Synthetase and Physicochemical Constants f o r 2 - P h e n y l - l , 3 - i n d a n e d i o n e s (3) Log 1/C,Uncoupling Log 1/ÏC5Q PGS, Calcd.d Log D Log D 0bsd. Calcd.b Obsd. PKa

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524

PH 7.5 l o g 1/C = - 0.41 ( l o g Ρ Γ + 0.21 l o g Ρ + 3.75 9

(28)

log P

Q

= 0.26

(n = 7, r = 0 . 9 6 3 , s = 0.245)

(29)

pH 8 . 5 l o g 1/C = - 0.16 ( l o g P)

9

+ 0.58 l o g Ρ + 3.06

log

Ρ = 1.85 ο (η = 6, r = 0 . 9 9 7 , s = 0.108) Λ

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch023

3

The l o g P's i n these equations are f o r the c a l c u l a t e d p a r t i t i o n c o e f f i c i e n t s o f the sodium s a l t s (where l o g salt " 4 - 9 0 ) . These can a l s o be analyzed i n terms o f d i s t r i b u t i o n c o e f f i c i e n t s to obtain eq 30. The l o g D obtained should apply a t any pH i n c o n t r a s t to l o g P . Because the α-hydroxy a c i d s a l l have the same pK there i s no way to assess the e f f e c t o f a c i d i t y (or c o r r e l a t e d p r o p e r t i e s ) on b a c t e r i o ­ static activity. Any e l e c t r o n i c f a c t o r i s buried i n the c o n s t a n t . p

=

p

0

0

a

pH 7 . 5 , 8 . 5 l o q 1/C = - 0.102 ( l o g D) + 0.483 l o g D + 2.962 (6.91) (9.55) 9

(30)

log D0 = 2.36 (n = 1 3 , r = 0 . 9 5 0 , s = 0.288, F = 46) A few years ago Sheu and a s s o c i a t e s (25J reported the b a c t e r i o s t a t i c a c t i v i t y o f a v a r i e t y o f c a r b o x y l i c a c i d s with p K ' s c o v e r i n g a range o f 2 1/2 u n i t s . The monocarboxylic a c i d a c t i v i t i e s ys^. B. s u b t i l i s , are l i s t e d i n Table V I I I . Regression a n a l y s i s shows t h a t a c i d i t y i s important f o r a c t i v i t y . Equation 31, with eq 3 , p r e d i c t s t h a t the greater the a c i d i t y o f an a c i d of a given l o g P, the more potent i t w i l l be i n i n h i b i t i n g b a c t e r i a l growth. Even though the more a c i d i c compound w i l l be present i n lower c o n c e n t r a t i o n s i n b a c t e r i a l l i p i d biophases, some aspect r e l a t e d to i o n i z a t i o n i s important enough f o r a c t i v i t y to more then overcome t h i s disadvantage. Carboxylic a c i d s d i f f e r i n t h i s respect from phenols, a t l e a s t n i t r o p h e n o l s (eq 1 4 , 1 5 ) . Two d i a c i d s (Table V I I I ) are more a c t i v e than p r e d i c t e d by eq 3 1 . a

(31)

l o g l/ICcn = 0.479 l o g D - 0.713 pK + 5.539 (8.58) (8.53) a

& u

(n = 15, r = 0 . 9 5 5 , s = 0 . 2 4 1 , F = 63)

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

SCHERRER AND HOWARD

23.

Electronic

Factors

in

QSAR

525

Table V I I I I n h i b i t i o n o f B. s u b t i l i s by Carboxylic Acids and Physicochemical Constants f o r Eq 3 1 . Log

Acid

CH C0 H -0.17 C H C0 H 0.33 C3H C0 H 0.79 C HnC0 H 1.88 C H C0 H 2.98 C H C0 H 4.09 CH3CH=CHC0 H 0.72 CH CH=CHCH=CHC0 H1.46 C" H C0 h "»H 1.87 3

2

2

5

2

2

7

5

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch023

Log Ρ

2

7

15

2

q

19

2

2

3

2

6

5

2

4-H0C6H4C0 H 1.58 4-HOCfiH/ C H CH C0 R 1.41 C H5CH=CHC0 H 2.13 2-H0C H4C0 H 2.26 2-Ac0C H4C0 H 1.23 3,5-I -2-H0C H C0 H 4.56 2

6

5

2

2

6

2

6

2

6

2

2

6

2

2

2

2

4

0.08 0.61

2

2

R e f e r e n c e 25.

a

b

Log

D

6 - 5

0bsd.

a

Calcd.

1

4.76 4.87 4.87 4.87 4.88 4.90 4.69 4.70 4.20 4.58 4.29 4.44 2.97 3.50

-1.91 -1.30 -0.84 0.25 1.36 2.49 -1.09 -0.34 -0.43 -0.34 -0.80 0.07 -1.27 -1.77

1.19 1.40 1.52 1.96 2.74 3.60 1.70 1.96 2.20 1.92 2.10 2.52 3.00 2.70

1.23 1.45 1.67 2.19 2.71 3.24 1.68 2.03 2.34 2.11 2.10 2.41 2.82 2.20

2.33

0.39

3.70

4.07

4.42,5.41 - 3 . 2 0 4.48,5.42 -3.13

1.46 1.82

(0.86) (0.85)

2

H0 C(CH ) C0 H H0 C(CH )5C0 H 2

pK

I/IC50

E q u a t i o n 31.

Concluding Remarks The wide range of examples we have presented using l o g D tend to support the broad view t h a t d i s t r i b u t i o n c o e f f i c i e n t s f o r i o n i z a b l e compounds are the natural counterpart of p a r t i t i o n c o e f f i c i e n t s f o r neutral compounds. The use of l o g D i s p a r t i c ­ u l a r l y advantageous i n the f o l l o w i n g circumstances: ( i ) when a n a l y z i n g s e r i e s c o n t a i n i n g i o n i z e d and unionized compounds, or c o n t a i n i n g both a c i d s and bases; ( i i ) when c o n s o l i d a t i n g data obtained a t more than one pH; and ( i i i ) when s o r t i n g out e l e c ­ t r o n i c , s t e r i c or other e f f e c t s on d i s t r i b u t i o n from those a s s o c i a t e d with a mechanism or s i t e o f a c t i o n .

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COMPUTER-ASSISTED DRUG DESIGN

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Literature Cited 1. Scherrer, R.A. and Howard, S.M., J. Med. Chem. (1977), 20,53. 2. Timmermans, P.B.M.W.M. and van Zwieten, P.Α., J. Med. Chem. (1977), 20, 1636. 3. Coats, E.A., Milstein, S.R., Pleiss, M.A. and Roesener, J.Α., J. Med. Chem. (1978), 21, 804. 4. Al-Gailany, K.A.S., Houston, J.B. and Bridges, J.W., Biochem. Pharmacol. (1978), 27, 783. 5. Lien, E.J. in "Drug Design," Vol. V, E.J. Ariëns, Ed., Academic Press, New York, N.Y., 1975, pp 81-132. 6. Beckett, A.H. and Moffat, A.C., J. Pharm. Pharmacol. (1968), 20, 239S; (1969), 21, 139S. 7. Lien, E.J., Koda, R.T. and Tong, G.L., Drug Intel. (1971), 5, 38. 8. Schürmann, W. and Turner, P., J. Pharm. Pharmacol. (1978), 30, 137. 9. Buchel, K.H. and Draber, W., in "Biological Correlations-The Hansch Approach", pp. 141-154. Advances in Chemistry Series 114, American Chemical Society, Washington, D.C., 1972. 10. Draber, W., Büchel, K.H. and Schäfer, G., Z. Naturforsch (1972), 27, 159-171. 11. Kessler, R.J., Tyson, C.A. and Green, D.E., Proc. Natl. Acad. Sci. USA (1976) 73, 3141. 12. Tollenaere, J.P., J. Med. Chem. (1973), 16, 791. 13. Stockdale, M. and Selwyn, Μ., Eur. J. Biochem. (1971), 21,565. 14. Norrington, F.E., Hyde, R.M., Williams, S.G. and Wootton, R., J. Med. Chem. (1975) 18, 604. 15. Motais, R., Sola, F. and Cousin, J.L., Biochim. Biophys. Acta (1978), 510, 201. 16. Cowles, P.B. and Klotz, I.M., J. Bacteriol. (1948), 56, 277. 17. Fujita, T., J. Med. Chem. (1966), 9, 797. 18. Weinbach, E.C. and Garbus, J., J. Biol. Chem. (1965), 240, 1811. 19. Hansch, C., Kiehs, K. and Lawrence, G.L., J. Am. Chem. Soc. (1965), 87, 5770. 20. Terada, H., Muraoka, S. and Fujita, T., J. Med. Chem. (1974), 17, 330. 21. van den Berg, G., Bultsma, T., Rekker, R.F. and Nauta, W.T., Eur. J. Med. Chem. (1975), 10, 242. 22. van den Berg, G., Bultsma, T. and Nauta, W.T., Biochem. Pharmacol. (1975), 24, 1115. 23. Eggerth, A.H., J. Exp. Med. (1929), 50, 299. 24. Hansch, C. and Clayton, J.M., J. Pharm. Sci. (1973), 62, 1. 25. Sheu, C.W., Salomon, D., Simmons, J . L . , Sreevalsan, T. and Freese, E., Antimicrob. Agts. Chemother. (1975), 7, 349. RECEIVED

June 8, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

24 Computer-Assisted Synthetic Analysis: The Merck Experience P. GUND, E. J. J. GRABOWSKI, and G. M. SMITH—Merck Sharp & Dohme Research Laboratories, Rahway, NJ 07065 J. D. ANDOSE and J. B. RHODES—Management Information Systems, Merck & Co., Inc., Rahway, NJ 07065

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

W. T. WIPKE—Board of Studies in Chemistry, University of California, Santa Cruz, CA 95060 In the decade since the first published description of a computer program capable of deriving synthetic routes to complex molecules,(1) the field has grown into a lively discipline.(2,3,4) Nevertheless, i t cannot yet be said that computer assisted synthesis is an accepted research tool for many practicing synthetic chemists. It is easy to see the appeal of computer aids to synthesis. Organic synthesis is complex; in principle several thousand reactions could be applied in several steps to millions of potential starting materials in order to prepare a desired product.(2,3) The computer has the capability of extending the chemist's perception and memory, and of systematizing and organizing his synthetic knowledge. While Merck has for a long time recognized the computer's potential in this area,(5) the decade was half over before the field was sufficiently advanced for an in-house effort to be considered. When a computer assisted synthesis project was begun, a number of major design decisions were quickly made. To assure data s e c u r i t y and to encourage optimal use, we wanted to run the program in-house. We wished to i n v o l v e the s y n t h e t i c chemists d i r e c t l y i n the analyses; t h i s meant i n t e r a c t i v e timeshared program operation on graphics terminals remote from the computer. This a l s o meant that s y n t h e t i c analyses would not be run e x c l u s i v e l y as a s c i e n t i f i c information s e r v i c e . F i n a l l y , by using the same graphics terminals f o r computer a s s i s t e d synthesis and f o r the Merck Molecular Modeling P r o j e c t , we could make more e f f i c i e n t use of our resources. A b r i e f survey of extant programs i n d i c a t e d that the Simulation and E v a l u a t i o n of Chemical Synthesis (SECS) program^) was most s u i t e d to Merck's needs· Today we are running SECS on our corporate IBM computer, with the program accessed by four graphics terminals i n three research l a b o r a t o r i e s (Rahway, New Jersey, West P o i n t , Pennsylvania and Montreal, Canada). About 60 chemists have been checked out on running SECS analyses, and the program i s 0-8412-0521-3/79/47-112-527$06.25/0 ©

1979 A m e r i c a n C h e m i c a l Society

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

528

used almost d a i l y . About 20 v o l u n t e e r chemists have c o n t r i b u t e d chemistry f o r the program, and two chemists are adding chemistry to the f i l e . At t h i s stage i n the program's development, i t i s approp r i a t e to report our experiences i n implementing, e v a l u a t i n g and enhancing the SECS program at Merck, and to review plans f o r f u t u r e development·

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

Implementation of SECS at Merck This s e c t i o n gives a r a t h e r t e c h n i c a l d i s c u s s i o n of how SECS was converted to run i n the Merck environment. We b e l i e v e that our experiences may prove h e l p f u l to others faced with the problem of converting large programs to operate on a l i e n comp u t e r s . Chemists u n i n t e r e s t e d i n the programming d e t a i l s may skip to the next s e c t i o n , on e v a l u a t i o n of program u t i l i t y . In October of 1974, we r e c e i v e d v e r s i o n 1.09 of the SECS program^»8.10)with supporting documentation. The source program c o n s i s t e d of approximately 25,000 l i n e s of code w r i t t e n f o r a D i g i t a l Equipment Corporation (DEC) PDP-10 computer ( c a . 20,000 l i n e s of FORTRAN w r i t t e n f o r DEC's F-40 compiler and about 5,000 l i n e s of assembly language code w r i t t e n i n MACRO-10) together with another 5,000 l i n e s of code to support a DEC GT-40 s e r i e s graphics d i s p l a y terminal ( w r i t t e n i n MACR0-11 assembly language f o r a PDP-11 minicomputer)· System l e v e l documentation c o n s i s t e d of short (1-2 pages) write-ups f o r each of the jça. 250 subroutines comprising the SECS system and b r i e f d e s c r i p t i o n s of the major data s t r u c t u r e s used throughout. In a d d i t i o n , we r e c e i v e d a p r e l i m i n a r y data base of approximately 250 chemical r e a c t i o n s w r i t t e n i n the ALCHEM language^)and t r e a t e d as data by the program. Our immediate o b j e c t i v e was to t r a n s l a t e the program i n t o code that would operate on our corporate IBM computer - at that time a model 370/155 - under the Time Sharing Option (TS0).(L1) General Implementation Approach. We d i v i d e d the program i n t o a number of smaller program modules, and then implemented each of these i n an order which would permit t e s t i n g of the program during the intermediate stages of assembly. Where p o s s i b l e , s e c t i o n s were tested independently p r i o r to i n t e g r a t e d testing· For the purposes of our implementation, the SECS program was d i v i d e d i n t o the modules l i s t e d i n Table I.(LQ) Implement a t i o n order dependencies ( f o r t e s t i n g purposes) f o r each module are shown g r a p h i c a l l y i n Figure 1. Of these modules, UTIL, GT42LIB, and SYNCOM were s e p a r a t e l y and independently t e s t a b l e . GT42M0N could be t e s t e d once GT42LIB was a v a i l a b l e , f o l l o w i n g which SIO could be t e s t e d . PERCV could not be tested u n t i l SIO and a l l of UTIL was a v a i l a b l e , whereas CHEM r e q u i r e d the a v a i l a b i l i t y of a l l of the preceding p l u s SYNCOM.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

24.

GUND E T A L .

The

Merck

Experience

Time

I

SIO

529 >

I

PERCY CHEM UTIL* GT42LIB*

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

GT42MON SYNCOM*

(*Separately

Testable) Figure 1.

SECS module testing dependencies

Implementation of the program, e s p e c i a l l y through the intermediate stages, was g r e a t l y f a c i l i t a t e d by three f a c t o r s . F i r s t , the program contained extensive b u i l t - i n debugging f a c i l i t i e s which could be s e l e c t i v e l y a c t i v a t e d by s e t t i n g appropriate "debug" switches as part of the input options i n SIO. Second, a working v e r s i o n of the SECS program, a v a i l a b l e through a commercial time-sharing service,(12) could be used t o compare debug output from our v e r s i o n , allowing the d e t e c t i o n of s u b t l e e r r o r s introduced during the implementation process. F i n a l l y , Professor W. T. Wipke was a v a i l a b l e as a p r o j e c t consultant f o r a s s i s t i n g with d i f f i c u l t problems. Implementation D e c i s i o n s . A number of d e c i s i o n s were made during implementation of the SECS program which r e f l e c t d i f f e r e n c e s between our computer environment and o b j e c t i v e s , and those of the program originators· We decided t o reimple­ ment much of the assembly language code i n FORTRAN i n order to s i m p l i f y f u t u r e program maintenance and m o d i f i c a t i o n s . We a l s o decided to omit packing of the connection t a b l e f o r the target molecule (which saves about 10 Κ bytes) s i n c e we had l e s s s t r i n g e n t core l i m i t a t i o n s . S i m i l a r l y , we chose not to imple­ ment the disk-based v i r t u a l array storage package that came with the SECS program. Instead, we expanded the memory a l l o c a t i o n f o r the dynamic array a l l o c a t i o n routines and d i v e r t e d a l l v i r t u a l array storage package c a l l s to the dynamic array storage package. Again f o r s i m i l a r reasons, we chose not to overlay our implementation of the SECS program. The net e f f e c t of a l l these d e c i s i o n s was to i n c r e a s e the memory requirements f o r the

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG

530

DESIGN

Table I SECS Program Modules

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

Module

Description

SIO

G r a p h i c a l and keyboard input/output r o u t i n e s ; i n c l u d e s main command processor and d r i v e r routines·

PERCV

Perception r o u t i n e s ; analyze s t r u c t u r e f o r b a s i c s t r u c t u r a l f e a t u r e s ( r i n g s , f u n c t i o n a l groups, e t c . ) and a s s i g n a unique stereochemical name.

CHEM

Strategy r o u t i n e , transform i n t e r p r e t e r , precursor generator, precursor e v a l u a t i o n r o u t i n e s , s y n t h e s i s tree generator.

UTIL

General purpose u t i l i t y r o u t i n e s f o r dynamic array a l l o c a t i o n , l i s t p r o c e s s i n g , b i t packing and unpacking, and l o g i c a l s e t manipulation.

GT42LIB

General purpose, FORTRAN-caliable subroutine package to support graphics on a GT-40 s e r i e s graphics d i s p l a y t e r m i n a l , based on software developed by D i g i t a l Equipment C o r p o r a t i o n .

GT42M0N

GT-40 s e r i e s t e r m i n a l monitor program c o n t r o l s communication between graphics t e r m i n a l and host computer. Based on software developed by D i g i t a l Equipment C o r p o r a t i o n .

SYNCOM

Stand-alone program f o r converting d e s c r i p t i o n s of chemical r e a c t i o n s w r i t t e n i n ALCHEM i n t o an object code usable by the SECS program.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

24.

GUND E T A L .

The

Merck

Experience

531

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

SECS program from 240 Κ bytes (48 Κ words) on the PDP-10 t o approximately 620 Κ bytes on our IBM 370/168 computer. T h i s does not present a problem, however, s i n c e under IBM's v i r t u a l operating system,(Ll) each a p p l i c a t i o n program has a v a i l a b l e 16,000 Κ bytes of s t o r a g e . The most important implementation d e c i s i o n made was to make the minimal program changes necessary to get the program to r u n . Code o p t i m i z a t i o n and program enhancements were deferred u n t i l a f t e r a working v e r s i o n was a v a i l a b l e . F a i l u r e to s t r i c t l y adhere to t h i s p r i n c i p l e i n the e a r l y stages s i g n i f i c a n t l y added to the conversion e f f o r t and r e s u l t e d i n the i n t r o d u c t i o n of s e v e r a l e r r o r s which r e q u i r e d a d d i t i o n a l time to l o c a t e and remove· Implementation Problems. A d i s c u s s i o n of problems encountered during implementation of the SECS program f o l l o w s i n three p a r t s : problems i n converting the assembly language r o u t i n e s , problems i n i n t e r f a c i n g the DEC GT-40 s e r i e s graphics d i s p l a y terminal t o our IBM computer, and problems i n converting from DEC to IBM FORTRAN· Each of these problem areas w i l l be discussed s e p a r a t e l y , below. 1. Assembly Language Implementation. In g e n e r a l , no p r o ­ blems were encountered i n converting the DEC assembly language p o r t i o n s of the SECS program to run on the IBM computer. The program authors had a n t i c i p a t e d eventual conversion of t h e i r program to run on machines with reduced word s i z e . Care had been taken throughout the program to use no more than 32 of the 36 a v a i l a b l e b i t s of a computer word when packing data f o r s t o r a g e . Had t h i s not been the case, conversion of both the assembly language and the FORTRAN r o u t i n e s would have been s i g n i f i c a n t l y more complicated. With the exception of the f u n c t i o n a l group d e f i n i t i o n r o u t i n e (FGTAB) from the PERCV module, a l l other assembly language routines (from the UTIL and GT42LIB modules) are of the "software tool'1^3) v a r i e t y - i . e . , independent, general purpose r o u t i n e s which perform a s i n g l e , w e l l - d e f i n e d f u n c t i o n . Rather than attempt a l i n e by l i n e t r a n s l a t i o n from DEC's MACRO-10 assembly language to IBM's assembly language, we s t a r t e d with the f u n c t i o n a l d e f i n i t i o n of each r o u t i n e and recoded each from s c r a t c h . This gave us the f l e x i b i l i t y to implement these routines i n the most convenient language. Where we f e l t that execution speed would not be impacted too badly, we opted to code i n FORTRAN because of the greater ease of program maintenance. Thus, the dynamic array a l l o c a t i o n r o u t i n e s , the l i s t processing r o u t i n e s , and most of the GT42LIB r o u t i n e s were r e w r i t t e n i n FORTRAN. The b i t packing and unpacking routines and the l o g i c a l set manipulation r o u t i n e s were rendered i n t o IBM assembly language·

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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COMPUTER-ASSISTED DRUG DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

In the process of implementing the UTIL r o u t i n e s , whether i n FORTRAN or assembly language, extensive e r r o r checking of passed arguments was incorporated to f a c i l i t a t e the l o c a t i o n of e r r o r s introduced i n implementing other parts of the program. The UTIL r o u t i n e s are e x t e n s i v e l y c a l l e d throughout both the PERCV and CHEM modules. Since i t was l i k e l y that e r r o r s i n t r o duced i n implementation would r e s u l t i n "bad" arguments being passed to these r o u t i n e s , then by trapping such events and f o r c i n g a program termination with subroutine traceback, l o c a t i o n of the e r r o r i n PERCV or i n CHEM was s i m p l i f i e d . 2. GT-40 I n t e r f a c e . Our v e r s i o n of the SECS program uses a DEC GT-40 s e r i e s graphics d i s p l a y terminal f o r a l l input and output The software we r e c e i v e d to support the terminal was a modified v e r s i o n of DEC's GT-40L program. A c t u a l l y , GT-40L i s two programs. The f i r s t program, which we designate as GT42LIB, c o n s i s t s of a set of FORTRAN-callable subroutines w r i t t e n i n the DEC MACRO-10 assembly language. These subroutines are c a l l e d by the a p p l i c a t i o n program (SECS) and send graphics commands to the t e r m i n a l as encoded s t r i n g s of ASCII c h a r a c t e r s . The second program, GT42MON, w r i t t e n i n MACRO-11 assembly language, r e s i d e s i n the PDP-11 minicomputer which i s an i n t e g r a l part of the graphics t e r m i n a l . This program decodes the s t r i n g s of c h a r a c t e r s , converts them i n t o g r a p h i c a l images, and handles a l l communications between the terminal and the host computer. Our task i n i n t e r f a c i n g the GT-40 s e r i e s graphics terminal to our IBM 370 computer i n v o l v e d much more than a simple convers i o n of the MACRO-10 code i n t o IBM equivalent code. I t was necessary to modify the Telecommunications Access Method (TCAM) p o r t i o n of our IBM operating system to allow transmission of the f u l l ASCII character set ( i n c l u d i n g a l l c o n t r o l characters) to our terminal .(15) I t was necessary to modify a l l of the communic a t i o n code i n both GT42LIB and GT42MON to r e f l e c t d i f f e r e n c e s between the IBM and DEC p r o t o c o l s f o r communication with asynchronous terminals .(L6) As mentioned e a r l i e r , most of GT42LIB was r e w r i t t e n i n FORTRAN with those p o r t i o n s that a c t u a l l y transmit character data w r i t t e n i n IBM assembly language ^LZ) Since there i s no MACRO-11 cross compiler a v a i l a b l e on our IBM system, changes to GT42MON were made on a PDP-10 copputer accessed through 3. FORTRAN Implementation. Implementation of the FORTRAN s e c t i o n s of code involved removal of obvious syntax e r r o r s r e s u l t i n g from d i f f e r e n c e s between the DEC FORTRAN-40 and the IBM FORTRAN Gl language s p e c i f i c a t i o n s . Each s e c t i o n of code was compiled using the FORTRAN Gl compiler and the r e s u l t i n g output was scanned l i n e - b y - l i n e . Compiler detected incompata b i l i t i e s were removed by r e c o d i n g . Table I I summarizes the major language d i f f e r e n c e s which we encountered between the DEC and IBM FORTRAN d i a l e c t s . In

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

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general, the DEC language s p e c i f i c a t i o n provided many added, non-standard f e a t u r e s which were not a v a i l a b l e i n the IBM v e r s i o n , n e c e s s i t a t i n g s i g n i f i c a n t recoding e f f o r t . One p a r t i c u l a r d i f f e r e n c e i n the IBM and DEC FORTRAN implementations was not flagged by the compiler but was i s o l a t e d only with great d i f f i c u l t y during program t e s t i n g . In the DEC computer, the expression "A.EQ.B" i n v o l v e s a b i t by b i t comparison of A with Β f o r a l l data types. Under the IBM com­ p i l e r , however, f o r s i n g l e and double p r e c i s i o n r e a l ( f l o a t i n g p o i n t ) v a r i a b l e s , i f the f r a c t i o n a l components of A and Β both evaluate as zero, then A and Β are considered equal no matter what the b i t p a t t e r n f o r the exponents (the f i r s t eight b i t s ) . In o r d i n a r y usage, t h i s would create no problems. In the SECS program, however, double p r e c i s i o n v a r i a b l e s represent not f l o a t i n g point numbers but sets of data, with each b i t p o s i t i o n representing a d i f f e r e n t element i n the s e t . Therefore, under the IBM compiler, two sets with b i t p o s i t i o n s 9 through 63 equal to zero always compare as equal no matter what the i n d i v i d u a l b i t patterns f o r p o s i t i o n s 1 through 8. Once t h i s problem was i d e n t i f i e d , i t was e a s i l y r e c t i f i e d by coding an assembly language f u n c t i o n EQV (SET 1, SET 2) which returns .TRUE, when SET 1 i s equivalent to SET 2 and .FALSE, otherwise. Implementation of the SECS program i n our IBM computer environment spanned an 18 month p e r i o d . This i n c l u d e d time to l e a r n IBM, PDP-10 and PDP-11 assembler languages; to l e a r n the d e t a i l s of how the SECS program was o p e r a t i n g ; and to solve the IBM-GT40 communications problem. A l s o , time was l o s t when our h e a v i l y used time-sharing system gave c o n s i s t e n t l y poor response. Nevertheless, f a r too much time was spent i n con­ v e r t i n g incompatible d i a l e c t s of the FORTRAN language. The authors would l i k e to add t h e i r v o i c e to that of Professor Beebe(LS.)in proposing s t r i c t adherence to ANSI standard FORTRAN. We f e e l , however, that the 1966 standard(L2) i s f a r too r e s t r i c t i v e , e s p e c i a l l y f o r non-numerical programming a p p l i ­ c a t i o n s , and we urge computer manufacturers to r a p i d l y adopt the 1977 ANSI standard FORTRAN^) Most importantly, we urge a l l manufacturers who extend t h i s standard i n the f u t u r e to b u i l d an o p t i o n i n t o t h e i r compilers to f l a g a l l use of extensions to the standard. We b e l i e v e that i t would take much l e s s time to reimplement the program today - both because of the problems which we have solved i n a general way, and because the current v e r s i o n of SECS i s c l o s e r to ANSI standard FORTRAN. I t i s p o s s i b l e that a p r e ­ processor program could a u t o m a t i c a l l y remove many of the FORTRAN inconsistencies· I t i s noteworthy that the data base of chemical r e a c t i o n s w r i t t e n i n ALCHEM which we r e c e i v e d , needed no m o d i f i c a t i o n s f o r use with our IBM v e r s i o n of SECS. The d e s c r i p t i o n of chemistry was thus independent of machine d i f f e r e n c e s described above.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Input/Output : Number of Characters/Word Dynamic F i l e A l l o c a t i o n Free Format Input of Character Data P a r t i a l Input of V a r i a b l e s i n Free Format Required Input f o r Each Item i n Input L i s t Special Carriage Control Characters i n FORMAT Statement ENCODE/DECODE

Boundary Alignment:

Memory I n i t i a l i z a t i o n : Data I n i t i a l i z a t i o n : Variables i n COMMON

Word Length: Single P r e c i s i o n Double P r e c i s i o n

Feature

DATA statements can appear i n any r o u t i n e . No

Requires Separate BLOCK DATA r o u t i n e .

Yes No; omitted items d e f a u l t to z e r o . Yes; $ i n FORMAT statement suppresses c a r r i a g e r e t u r n and l i n e f e e d . Yes

No

Yes

No

No

5 Yes Yes

4 No No

Required (imposes r e s t r i c t i o n s on ordering of v a r i a b l e s i n COMMON)

36 b i t s 72 b i t s (molecule of 72 atoms accommodated) I n i t i a l i z e d to zero.

DEC F-40 FORTRAN

32 b i t s 64 b i t s (molecule of 64 atoms accommodated) None

IBM FORTRAN G l

FORTRAN D i f f e r e n c e s

Table I I

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

B i t by b i t comparison except f o r f l o a t i n g p o i n t v a r i a b l e s whose f r a c t i o n s both evaluate as z e r o . (Refer to text f o r consequences i n SECS program.)

Implementation of .EQ. :

Array I n d i c e s :

Integer expressions not p e r m i t t e d . Loop increment must be p o s i t i v e integer. Lower bound i s one.

Logical

Allowed i n DATA and FORMAT statements only. S t r i c t s e p a r a t i o n e n f o r c e d . In l o g i c a l I F , operators .AND., .OR., •NOT. must be used with l o g i c a l v a r i a b l e s only while .EQ., .LT., •GT. must be used with i n t e g e r variables only.

IBM FORTRAN Gl

(Continued)

DO Loop Bounds :

Integer vs·

Data Types: H o l l e r i t h Constants

Feature

Table I I

F-40

FORTRAN

A l s o allowed i n ASSIGNMENT and IF statements. No s t r i c t s e p a r a t i o n . No need to d e c l a r e l o g i c a l v a r i a b l e s . Operators .AND., .OP., .NOT., .EQ. operate b i t by b i t comparison f o r i n t e g e r variables· Integer value 0 corresponds to .FALSE, while -1 evaluates as .TRUE. Integer expressions p e r m i t t e d . Loop increment can be p o s i t i v e or n e g a t i v e . Can s p e c i f y lower and upper bounds f o r range ( p o s i t i v e or negative)· B i t by b i t comparison f o r a l l data types·

DEC

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

COMPUTER-ASSISTED

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

536

DRUG DESIGN

Following our implementation of the SECS program and based on our experiences i n using the program i n a production e n v i r o n ment (see below), we i n c o r p o r a t e d a number of enhancements i n t o our v e r s i o n of SECS. These enhancements i n c l u d e a more streaml i n e d (continuous drawing) format f o r molecule input using a l i g h t pen, the o p t i o n to s e l e c t i v e l y d i s p l a y at the t e r m i n a l only those s t r u c t u r e s which s u c c e s s f u l l y pass e v a l u a t i o n , b r i g h t e n i n g of l i n e s i n the s y n t h e s i s tree corresponding to s t r u c t u r e s which have been rated "GOOD", and l a s t l y , a hard copy (Calcomp) summary of the r e s u l t s of an a n a l y s i s . A l l of these enhancements have a l s o been i n c o r p o r a t e d i n t o subsequent v e r s i o n s ^ ) o f the parent SECS program at Santa Cruz by P r o f e s s o r Wipke, although s e v e r a l (such as hard copy) were implemented i n a d i f f e r e n t manner. E v a l u a t i o n of Program U t i l i t y Once SECS was implemented and running at Merck, i t was necessary to i n v o l v e the chemists i n e v a l u a t i n g the program's u t i l i t y . However, we were concerned that without being given background i n f o r m a t i o n , a chemist might see one or two poor SECS analyses and dismiss the methodology out of hand. In essence, we were asking the chemists to evaluate the u t i l i t y of an eventual "production" system based on the current developmental system. In order to make such an e v a l u a t i o n v a l i d l y , we f e l t the chemists needed some background i n how the program a c t u a l l y operated. Consequently, i n the F a l l of 1976 we organized a course f o r p a r t i c i p a t i n g chemists. A t o t a l of 25 s e n i o r l e v e l chemists from s i x departments i n Rahway (Basic Synthetic Research; Process Research; New Leads Discovery; A r t h r i t i s & A n t i inflammatory Research; Membrane Chemistry; and Radiochemistry) attended. The m a t e r i a l (Table I I I ) , presented i n 15 one-hour Table I I I Merck Course on Computer A s s i s t e d Organic Synthetic A n a l y s i s 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.

Overview of the f i e l d . Overview of SECS program (W. T. Wipke - 3 h o u r s ) . Program o p e r a t i o n ; i n t r o d u c t i o n to IBM time-sharing (TSO). Review of t y p i c a l s y n t h e t i c a n a l y s i s . Program modules, molecule drawing, s t r u c t u r e representation. Molecule p e r c e p t i o n . What i s a transform? Transform types. D e t a i l e d walk-through of a coded transform. Precursor e v a l u a t i o n , s t r a t e g y . Model b u i l d i n g , s t e r i c and aromatic e f f e c t s . W r i t i n g a transform.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

l e c t u r e s was d e t a i l e d enough to d i s p e l some of the mystery about how a computer can " p e r c e i v e " a chemical s t r u c t u r e , "remember" chemical r e a c t i o n s and "suggest" p o s s i b l e p r e c u r s o r s . Despite the heavy t e c h n i c a l content and the chemists' busy schedules, a l l p a r t i c i p a n t s but one completed the course. One chemist who was t r a n s f e r r e d to Merck's West P o i n t , Pennsylvania l a b o r a t o r i e s commuted one day a week to Rahway i n order to complete the course. A s p i n - o f f from preparing the l e c t u r e m a t e r i a l s was a comprehensive SECS user's manual. The f i r s t l e c t u r e was a l s o published 4L) In a d d i t i o n to attending the l e c t u r e s , each p a r t i c i p a n t attended workshops i n groups of f i v e and used the program on r e a l s y n t h e t i c problems. Each chemist performed at l e a s t 2 analyses, f o r a t o t a l of over 50. For perhaps two out of three compounds analyzed, nothing u s e f u l was d i s c o v e r e d . O c c a s i o n a l l y , however, r e a l l y novel approaches were found to current s y n t h e t i c o b j e c t i v e s . Some noteworthy analyses are reviewed i n the next section. When the course was f i n i s h e d , we asked the p a r t i c i p a n t s to complete questionnaires and w r i t e e v a l u a t i o n s of the p r o j e c t . We r e c e i v e d 22 completed (anonymous) questionnaires and 15 r e p o r t s . In the F a l l of 1977, a f t e r a t e r m i n a l was i n s t a l l e d i n West P o i n t , the course was repeated f o r 21 M e d i c i n a l Chemistry Department chemists. At the c o n c l u s i o n of t h i s course, 16 questionnaires were r e t u r n e d . The f o l l o w i n g conclusions emerged from the chemists' evaluations· 1. The methodology o f f e r s great promise f o r a i d i n g synt h e t i c design. The system can improve and extend the chemist's own a n a l y t i c a l a b i l i t i e s , and s t i m u l a t e the c o n s i d e r a t i o n of new approaches. However, i t can n e i t h e r supplant the s y n t h e t i c chemist nor r e l i e v e him of the task of working out a d e t a i l e d synthetic plan. 2. Our system hardware i s a c c e p t a b l e . Using the l i g h t pen to " p o i n t " to the GT42-GT43 d i s p l a y screen i s a convenient input method f o r the chemist. The IBM time-shared system (TSO) presented some problems f o r the computer-naive chemist (e.g., c r y p t i c e r r o r messages), and o f t e n s u f f e r e d from poor response times; at other times the system was q u i t e s a t i s f a c t o r y . S i m i l a r l y , the SECS program design was considered e x c e l l e n t . There was a strong d e s i r e f o r hard copy summary of analyses (one member of each workshop recorded each a n a l y s i s ; automatic a n a l y s i s summary on the p l o t t e r became a v a i l a b l e a f t e r the Rahway course was over)·

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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538

3. The v e r s i o n of SECS (1.0) which we implemented(9)was considered to need extensive f u r t h e r development. The chemists found that the p r e l i m i n a r y data base needed expansion and r e v i s i o n . T h i s was expected, s i n c e the s u p p l i e d transforms had been w r i t t e n by the system developers to e x e r c i s e v a r i o u s pro­ gram f e a t u r e s r a t h e r than i n a systematic attempt to cover the f i e l d of s y n t h e t i c organic chemistry. The chemists a l s o f e l t that the a n a l y s i s was too automated; they wanted more c o n t r o l over what chemistry was a p p l i e d (more recent v e r s i o n s of SECS have high l e v e l s t r a t e g i e s f o r t h i s purpose). Many other, r e l a ­ t i v e l y minor complaints and suggestions were made. 4. I t was widely b e l i e v e d that such a d e t a i l e d course was not necessary f o r l e a r n i n g how to operate the SECS program. Since the completion of the courses, chemists have con­ tinued to p a r t i c i p a t e i n the p r o j e c t , by improving the data base of r e a c t i o n s (as d i s c u s s e d below) and by using the program. During 1978, monthly use of the program ranged from a low of 6 to a high of 71 runs. T h i s year, we have o f f e r e d f i r s t l e v e l SECS analyses as a s e r v i c e , s i m i l a r to the way Dr. B e r y l Dominy runs the program at P f i z e r Corporation;£ί^ t h i s has been w e l l received · We p l a n to implement a more up-to-date v e r s i o n of SECS at Merck, and (as discussed below) we are working to improve and expand the program's chemical knowledge. As the software improves, we expect SECS to gain i n c r e a s i n g acceptance here as a research t o o l . D i s c u s s i o n of Selected Analyses A review of the Merck experience with computer a s s i s t e d s y n t h e s i s would be incomplete without some d i s c u s s i o n of a c t u a l r e s u l t s which have been generated by SECS. In doing so, one must remember that we are not working with a " f i n i s h e d product", but instead with a developing research t o o l which i s the sub­ j e c t of current research e f f o r t s , and that our analyses are based on software which was " s t a t e - o f - t h e - a r t " i n 1974^) S t i l l , the best way to gain i n s i g h t i n t o the strengths and weaknesses of the s y n t h e s i s program at t h i s stage i n i t s development i s by c o n s i d e r i n g the r e s u l t s of a few s p e c i f i c a n a l y s e s . S t r u c t u r e _1 represents the nucleus f o r the new Merck product C L I N O R I L C U and was our f i r s t candidate f o r a computer s y n t h e s i s t r i a l . I t was an e x c e l l e n t t e s t , because the SECS program was not p a r t i c u l a r l y developed f o r a n a l y z i n g s t r u c t u r e s such as 1· Furthermore an extensive body of chemistry had been developed f o r s t r u c t u r e s l i k e 1^ p r i o r to the SECS a n a l y s i s , so that the computer suggestions could be evaluated i n l i g h t of l a b o r a t o r y experience. F i n a l l y , 1^ remains an e x c e l l e n t target f o r new s y n t h e t i c approaches. Part of the a n a l y s i s developed by the chemists with the a i d of the computer i s summarized i n Scheme I .

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

During the i n i t i a l p r o c e s s i n g of 1 the s t a r r e d bonds (*) were i n d i c a t e d to be " s t r a t e g i c " bonds'!^) This proved most s a t i s f y i n g s i n c e one of the r e c e n t l y reported syntheses of CLINORIL ® i s based on the formation of these bonds Jfe2±2A) However, valence isomer 2^ was not recognized by SECS 1.0 as a precursor of 1^, and had to be processed s e p a r a t e l y . The combined processing of 1^ and 2 d i d generate the b a s i c elements of the synthesis of C L I N O R I L ® discussed i n reference 23. However,

Scheme I

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

540

one key point missed by SECS i s the a c i d i t y of ^3 and i t s amenab i l i t y to base catalyzed condensations. SECS d i d propose 3 as a precursor of 2* ^ by r e t r o - s y n t h e t i c W i t t i g and NBS r e a c t i o n s . The f a i l u r e of SECS to recognize e i t h e r the a c i d i t y of 3, o r the v i a b i l i t y of 2 as a precursor to 1_ simply r e f l e c t d e f i c i e n c i e s i n the r e a c t i o n data base at the time of the a n a l y s i s , as opposed to any d e f e c t s i n the program's o v e r a l l strategy. Processing of intermediate J5, which derived from 1^ v i a r e t r o - s y n t h e t i c W i t t i g and o x i d a t i o n r e a c t i o n s , gave r i s e to precursors 6^ and J^. A p r i o r i , the complex s t r u c t u r e s 6^ and J7 (having 4 and 3 c h i r a l c e n t e r s , r e s p e c t i v e l y ) , would appear to be poor precursors of the a c h i r a l t a r g e t s t r u c t u r e 1^. However, the suggestion of £ and 7_ by the synthesis program i n c i t e d chemists working on the problem to t h i n k about fragmentation processes as a route to 1^. Such processes had not been cons i d e r e d p r e v i o u s l y because of the planar nature of 1^· As an outgrowth of the SECS a n a l y s i s of 1^, r e a c t i o n s suggested by the arrows i n s t r u c t u r e s 9. and 10 were proposed by the chemists as p o s s i b l e precursors to 1· Although these proposals d i d not i n f a c t lead t o a s i g n i f i c a n t new synthesis of 1^, t h i s example i l l u s t r a t e s the program's a b i l i t y to induce chemists to think about new approaches to f a m i l i a r s y n t h e t i c problems.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

u t

w

a

v

o

f

In another example, a simple route to s t r u c t u r e 11, which has not been reported i n the l i t e r a t u r e , was d e s i r e d to support a p o s s i b l e s y n t h e t i c program. A s e s s i o n on the terminal l e d the chemist to propose compound JL2 as a l i k e l y precursor (Scheme II)· A l i t e r a t u r e search i n d i c a t e d i t s ready p r e p a r a t i o n from malic a c i d , thus, p r o v i d i n g a simple s o l u t i o n to the problem.

Scheme II

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

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The p o t e n t i a l of computer s y n t h e s i s f o r f u l l y and systemat i c a l l y a n a l y z i n g routes to complex, p o l y c y c l i c molecules has been noted b e f o r e R e c e n t l y the chemistry of 5,11-diazaditwistanes has been e x t e n s i v e l y s t u d i e d i n these l a b o r a t o r i e s .^5) Compound L3, the key analog p r o v i d i n g entry i n t o t h i s s e r i e s , has been prepared from JL4 as i n d i c a t e d i n Scheme I I I . Not s u r p r i s i n g l y , t h i s approach was not suggested by SECS; indeed, the necessary h y d r i d e - t r a n s f e r r e a c t i o n was only discovered when thermolysis of ]A unexpectedly gave r i s e to 13^ However, an i n t r i g u i n g route v i a a double Mannich r e a c t i o n and ozonol y s i s of an appropriate cyclooctene d e r i v a t i v e (15) d i d r e s u l t (Scheme I I I ) . F u n c t i o n a l group p r o t e c t i o n i s u n a v a i l a b l e i n our current v e r s i o n of SECS; c o n s i d e r a t i o n of p r o t e c t i n g groups makes the a n a l y s i s of Scheme I I I somewhat l o n g e r .

CN

CM

Scheme III

Work with the 5,11-diazaditwistanes brought to mind the unknown, a l l - c a r b o n analog i n the homologous s e r i e s - t r i t w i s t a n e (16)· Computer p r o c e s s i n g of ]J5 produced the appealing D i e l s - A l d e r route shown i n Scheme IV. At present t h i s route and obvious r e l a t e d approaches have not been reduced t o p r a c tice.

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Scheme IV

Recently our SECS program was demonstrated t o Professor Ρ· Magnus while he was v i s i t i n g these laboratories.(26) He chose as a t a r g e t the n a t u r a l product Quadrone (20), which i s of current i n t e r e s t i n h i s research program. SECS p r o j e c t e d prepa­ r a t i o n of ^0 from 21 v i a a n i o n i c a l k y l a t i o n (Scheme V ) , and p r e p a r a t i o n of 21 from 22 v i a an i n t r a m o l e c u l a r Michael r e a c t i o n . The l a t t e r step solves the d i f f i c u l t problem of c r e a t i n g the t e t r a s u b s t i t u t e d center and could be combined with the a l k y l a t i o n to provide ^0 i n a s i n g l e s t e p . Using the b a s i c approach of t h i s SECS a n a l y s i s , and t a k i n g i n t o account pro­ t e c t i o n and p o s s i b l e s i d e r e a c t i o n s , Professor Magnus q u i c k l y proposed a d i f f e r e n t route to ^0 which had not been considered before and which i s a reasonable a l t e r n a t e to the routes which he had already p r o j e c t e d .

Scheme V

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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The few examples shown here, among many that have been done, a r e r e p r e s e n t a t i v e of our current program's strengths and weaknesses. Without exception these examples show the importance of the computer-chemist i n t e r a c t i o n , with the computer suggesting approaches and the chemist t h i n k i n g them through and r e f i n i n g them.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

Further Development of SECS a t Merck Our experiences i n using the SECS program i n d i c a t e d that f u r t h e r development was necessary f o r SECS to become r o u t i n e l y u s e f u l t o the s y n t h e t i c chemist · While development of new program f e a t u r e s and s t r a t e g i e s was deemed e s s e n t i a l , these tasks have so f a r been l e f t mainly i n the hands of Professor Wipke's research group. We at Merck have concentrated on a d i f f e r e n t task: expanding and c o r r e c t i n g the base of chemical r e a c t i o n information a v a i l a b l e to the program, and e s t a b l i s h i n g a system f o r e f f i c i e n t l y w r i t i n g r e a c t i o n transforms. Reaction D e s c r i p t i o n s . Before d i s c u s s i n g the work on data base expansion, a short d e s c r i p t i o n of the r e p r e s e n t a t i o n used f o r data storage i s i n o r d e r . The b a s i c u n i t of i n f o r m a t i o n i n the data base i s the transform J&jJ) which d e s c r i b e s , i n the r e t r o - s y n t h e t i c d i r e c t i o n , the s t r u c t u r a l changes caused by a chemical r e a c t i o n . Each transform c o n s i s t s of three s e c t i o n s ; 1. 2. 3.

Header Qualifiers Manipulations

The header contains the s u b s t r u c t u r e (groups or pattern) which must be present i n the molecule being processed (target molec u l e ) i n order f o r a transform to be a p p l i c a b l e . The q u a l i f i e r s are used t o determine i f the s t r u c t u r e being processed has f e a t u r e s which w i l l a f f e c t the course of the r e a c t i o n . They can change the f i n a l p r i o r i t y ( a r b i t r a r y r a t i n g score) of a precursor generated, o r may prevent a t r a n s form from being a p p l i e d a t a l l . The q u a l i f i e r s are o p t i o n a l ; by d e f i n i n g the scope and l i m i t a t i o n s of a r e a c t i o n , they give a transform i t s "chemical i n t e l l i g e n c e " . The manipulations s y m b o l i c a l l y modify the s t r u c t u r e under c o n s i d e r a t i o n to give a proposed s t a r t i n g m a t e r i a l . The transforms are described i n a s p e c i a l language, ALCHEM.Ê) T h i s was designed t o allow simple chemical s t a t e ments to access a l l of the perceived s t r u c t u r a l i n f o r m a t i o n i n the SECS program. An example of a statement i s : I f aldehyde

i s anywhere then add 100

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The o r g a n i z a t i o n of the r e a c t i o n i n f o r m a t i o n as data, separ a t e from the SECS program, and having i t s own language, allows transforms to be w r i t t e n , t e s t e d and modified e a s i l y . T h i s has enabled us to concentrate on adding and c o r r e c t i n g transforms without having to a l s o make changes to the SECS program i t s e l f · Supplied Reactions. The p r e l i m i n a r y data base which was r e c e i v e d with the SECS 1.0 program, c o n t a i n i n g approximately 250 transforms, was used unchanged i n the i n i t i a l e v a l u a t i o n phase described above. While many of these transforms gave e x c e l l e n t d e s c r i p t i o n s of chemical r e a c t i o n s , other transforms were not f u l l y developed at the time we obtained them. The r e s u l t s of the workshop analyses h i g h l i g h t e d some s p e c i f i c d e f i c i e n c i e s . The problem given highest p r i o r i t y by the p a r t i c i p a t i n g chemists was the presence of transforms which gave unacceptable r e s u l t s . The next highest p r i o r i t y item was missing r e a c t i o n s . A f t e r some d i s c u s s i o n a l i s t of 15 transforms was drawn up which represented the worst o f f e n d e r s . The most common f e a t u r e s of these transforms were the c h e m i c a l l y i n c o r r e c t a p p l i c a t i o n of a r e a c t i o n , excessive p r i o r i t y f o r an unimportant r e a c t i o n , and/or a p p l i c a t i o n of a r e a c t i o n d e s p i t e an i n t e r f e r i n g f u n c t i o n a l group. A prime example of t h i s was the PINACOL r e a c t i o n . The "bare-boned" transform which represented t h i s r e a c t i o n contained few q u a l i f y i n g statements, and r e q u i r e d only the presence of a carbonyl group i n the s t r u c t u r e being analyzed. Since no r e s t r i c t i o n s were placed on the environment of that group, i t could be a carbonyl i n an a c i d , ketone, aldehyde, amide, or e s t e r . The r e s u l t was that many u n r e a l i s t i c s t a r t i n g m a t e r i a l s were proposed as being converted to a t a r g e t s t r u c t u r e by the PINACOL r e a c t i o n . Once the problem was understood, i t was easy to add q u a l i f y i n g statements to p r o p e r l y r e s t r i c t the a p p l i c a t i o n of t h i s transform. The current v e r s i o n of SECS (2.7) uses higher l e v e l s t r a t e g i e s to r e s t r i c t the a p p l i c a t i o n of s i m p l i s t i c transforms. Since our v e r s i o n has a p r i m i t i v e s t r a t e g y s e c t i o n , we have been f o r c e d to put s t r a t e g i c cons t r a i n t s i n t o the transforms· Transform Review Workshops. Workshops were organized to d e a l with the l i s t of worst transforms. Attendance at the workshops, which met f o r an hour per week, was v o l u n t a r y and ranged from a low of 3 to a high of 15. The format of the workshops was i n f o r m a l but followed the f o l l o w i n g o u t l i n e : The transform to be reworked was announced i n advance, with l i t e r a t u r e references to the r e a c t i o n being covered. A person f a m i l i a r with ALCHEM (a "coder") gave a step by step walkthrough of a transform. The chemical and s t r u c t u r a l meaning of each statement was e x p l a i n e d , t r i g g e r i n g a wider d i s c u s s i o n of the scope and l i m i t a t i o n s of the r e a c t i o n . As new aspects of

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the r e a c t i o n were covered, the coder made notes on q u a l i f i e r s to be added or changed. One key o b j e c t i v e of the coder was to p r e vent d e t a i l e d d i s c u s s i o n of experimental c o n d i t i o n s which cannot be represented i n a transform. From the notes on the meeting, a new transform was w r i t t e n and t e s t e d by the coder. Finally, t h i s transform r e p l a c e d the o r i g i n a l . A f t e r the 15 transforms had been m o d i f i e d , a n o t i c e a b l e r e d u c t i o n i n the number of bad s t r u c t u r e s was observed i n analyses produced by SECS. From t h i s experience two p o i n t s became c l e a r : the chemists d i d not want to l e a r n ALCHEM, even though they were w i l l i n g t o v o l u n t e e r t h e i r time and knowledge to improve the chemistry data base; and some other format was r e q u i r e d to e f f i c i e n t l y c o l l e c t chemical information. Reaction Review Seminars. At t h i s point i t was decided to change the emphasis from s t r i c t l y transform c o r r e c t i n g to w r i t i n g new transforms. Reaction review seminars were i n s t i tuted, i n which a v o l u n t e e r chemist would s e l e c t any r e a c t i o n of which he had s p e c i a l knowledge and prepare a seminar on i t s synthetic u t i l i t y . The coder attended the seminar, and took notes ; the chemist a l s o s u p p l i e d h i s notes· The coder then wrote a transform or transforms and d i d p r e l i m i n a r y t e s t i n g . Next the chemist tested the performance of the transforms on target s t r u c t u r e s of h i s choosing. Based on the chemist's suggestions, the transform was c o r r e c t e d as o f t e n as necessary, and f i n a l l y added to the data base. The advantages of t h i s approach were that the speaker s e l e c t e d the r e a c t i o n s and so had more i n t e r e s t i n them, and that the seminar served to i n c r e a s e the current awareness of other chemists. The major disadvantage was our d i f f i c u l t y i n inducing chemists to v o l u n t e e r , s i n c e p r e p a r a t i o n f o r the seminar r e q u i r e d a great d e a l of time. While t h i s format l a s t e d f o r only a short w h i l e , i t r e s u l t e d i n s i g n i f i c a n t upgrading of the data base, as summarized below:

Speaker R. R. E. E.

A. W. D. J.

Firestone Ratcliffe Thorsett J . Grabowski

Length of Seminar (Hours) 4 2 1 1

Resulting

Transform(s)

1-3 D i p o l a r A d d i t i o n s -Lactam Preparations Ni-Coupling Reactions Enamine Rearrangement

(30) (12) (3) (1)

Current Transform W r i t i n g Procedures. At t h i s point we h e l d a p r o j e c t review meeting with the chemists to assess p r o gress and point f u t u r e d i r e c t i o n s . The chemists f e l t they would l i k e to continue to improve the data base, and Dr. Tom B e a t t i e suggested that we send a memo to each Merck chemist asking f o r volunteers to summarize r e a c t i o n s f o r transform w r i t i n g . Response was g r a t i f y i n g ; about 60 chemists volunteered to h e l p .

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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To f a c i l i t a t e t h i s approach, we created a " r e a c t i o n summary form" which was designed to a s s i s t the chemist and the coder i n focusing on those aspects of a r e a c t i o n which are important f o r transform w r i t i n g . European companies running SECS have independently developed a s i m i l a r f o r m . Ê Z ) To f u r t h e r c l a r i f y the type of information r e q u i r e d , a seminar was given on how to f i l l out the form - using an example of a r e a c t i o n which had been w r i t t e n up as a transform. At the seminar a request was made f o r volunteers and 19 chemists agreed to p a r t i c i p a t e . The 15-page summary form c o n s i s t s of s e v e r a l s e c t i o n s , each focusing on a d i f f e r e n t type of s t r u c t u r a l f e a t u r e . The f i r s t s e c t i o n requests r e a c t i o n name, l i t e r a t u r e references, and a general equation. The next s e c t i o n i s f o r a d e t a i l e d d e s c r i p t i o n of the product s u b s t r u c t u r e . Here the e f f e c t of p o s s i b l e s u b s t i t u e n t s on the b a s i c substructure and on r e a c t i o n y i e l d should be considered. Next the s t a r t i n g m a t e r i a l s are s i m i l a r l y d e s c r i b e d . The f o l l o w i n g s e c t i o n i s concerned with how r i n g s a f f e c t the r e a c t i o n , and whether the r e a c t i o n i s i n t e r m o l e c u l a r , intramolecular or e i t h e r . The next s e c t i o n requests information on i n t e r f e r i n g f u n c t i o n a l groups, and how unsaturation a f f e c t s the r e a c t i o n . The l a s t s e c t i o n concerns experimental d e t a i l , which i s described as comments i n the transform. There i s a l s o a request f o r s e v e r a l t e s t s t r u c t u r e s and how w e l l the r e a c t i o n works f o r t h e i r s y n t h e s i s . I t takes chemists 1-5 days to summarize one r e a c t i o n ; approximately one week i s required f o r a coder to incorporate the information on the form i n t o a working transform. Addit i o n a l time i s required f o r the chemist to t e s t the transform and the coder to make c o r r e c t i o n s . The procedure at t h i s p o i n t seems to be accepted by the chemists. One point which i s emphasized by the chemists i s the need f o r current references to each r e a c t i o n . This process of c o l l e c t i n g chemical information from experienced chemists and i n c o r p o r a t i n g i t i n t o transforms has d r a m a t i c a l l y improved the q u a l i t y of the analyses produced by SECS. However there are s t i l l gaps i n the program's knowledge of most r e a c t i o n s and t h i s i s r e f l e c t e d i n i n c o r r e c t a p p l i cations of some transforms. The r e s u l t i s that the process of transform w r i t i n g must be i n t e r a c t i v e and c o n t i n u i n g . I f a major point has been overlooked or a new f a c t i s learned about a r e a c t i o n and the d e f i c i e n c y comes to l i g h t i n an a n a l y s i s , the transform must be modified and r e t e s t e d . As new f a c t s are incorporated and c o r r e c t i o n s made based on experience, the program's chemical knowledge can be expected to become c o n t i n u a l l y more s o p h i s t i c a t e d . Writing a transform i s s i m i l a r to w r i t i n g a computer program. When there i s a large amount known about a r e a c t i o n , the r e s u l t can be a very long and l o g i c a l l y complex s t r u c t u r e . In order to streamline t h i s procedure, i t has been d i v i d e d i n t o s e v e r a l

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

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steps, a l l o w i n g the s t r u c t u r e of the transform t o grow i n a way which f a c i l i t a t e s t e s t i n g a t each s t a g e . The f i r s t step i s to w r i t e the framework which c o n s i s t s of preceding comments ( r e f e r e n c e s , c o n d i t i o n s , e t c . ) , name, subs t r u c t u r e , i n i t i a l p r i o r i t y and manipulations. This i s then t e s t e d with s e v e r a l t e s t s t r u c t u r e s to make sure that the b a s i c transform i s c o r r e c t . Next, q u a l i f i e r s are added t o exclude obvious problems, such as valence v i o l a t i o n s o r simple s t e r i c requirements. F i n a l l y more s o p h i s t i c a t e d s t r u c t u r a l e f f e c t s are noted and coded i n t o q u a l i f i e r s . The transform i s t e s t e d a t each step with s t r u c t u r e s which w i l l e x e r c i s e each new f e a t u r e . At some p o i n t i n the coding of a transform the question a r i s e s : how much d e t a i l i s r e q u i r e d t o give new ideas without producing nonsense r e s u l t s ? To even consider t h i s q u e s t i o n , a second question must be answered; what are the goals of the chemist who i s using the program? I f he i s searching f o r new ideas i n the s y n t h e s i s of a compound, then the transforms should be w r i t t e n without too much d e t a i l . The r e s u l t i n g a n a l y s i s w i l l be a l a r g e r and more general (but not s t r i c t l y p r a c t i c a l ) p r e s e n t a t i o n of ideas which would have to be r e f i n e d f u r t h e r by the chemist. However i f a chemist i s l o o k i n g f o r a r e a c t i o n to perform a s p e c i f i c task, he wants to know the known l i m i t s of the r e a c t i o n . Here the r e s u l t s w i l l be a simpler a n a l y s i s showing the a p p l i c a t i o n of a few s p e c i f i c transforms. Since a s i n g l e data base i s p r e f e r r e d and s i n c e the chemists who use the system have a wide range of requirements, the transforms w r i t t e n at Merck tend t o be somewhere between the extremes d e s c r i b e d . One problem with attempting t o i n c l u d e too much d e t a i l i s that there are l i m i t s to what can e a s i l y be expressed i n the ALCHEM language, as discussed below. Several p o i n t s have become c l e a r during the two years which t h i s work covered. F i r s t and foremost, experienced chemists must be i n v o l v e d i n the development of the transform data base not only to supply the i n f o r m a t i o n on r e a c t i o n s but a l s o t o recommend the types of r e a c t i o n s to be i n c l u d e d . I t i s c l e a r from the current analyses produced by SECS that many more t r a n s forms - perhaps 2-3 times the present number - must be added before a reasonably thorough a n a l y s i s of a s t r u c t u r e can be produced. We have a l s o learned that chemists are not g e n e r a l l y w i l l i n g t o l e a r n ALCHEM, even enough to understand why a t r a n s form i s misbehaving; but they w i l l t e l l us which transforms need f u r t h e r work, and why. One of the key items which a transform should c o n t a i n i f i t i s to be t r u l y u s e f u l i s a l i s t of up-to-date r e f e r e n c e s . T h i s r a i s e s the major question of how best to maintain and r e t r i e v e the references i n a l a r g e and growing data base.

American Chemical Society Library 1155 16th St., N.W.

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548

Our e f f o r t s to w r i t e new transforms have increased substant i a l l y i n the past year with the a d d i t i o n of to our group of a s y n t h e t i c chemist, Dr. Dale Hoff, who can both summarize r e a c t i o n s and code transforms. The current Merck SECS data base contains over 500 transforms. The ALCHEM languageÊ)has proved to be general enough and f l e x i b l e enough to d e s c r i b e every r e a c t i o n which we have considered, i n E n g l i s h - l i k e sentences which are reasonably i n t e l l i g i b l e to chemists. Nevertheless the vocabulary of organic chemists i s very r i c h , and some concepts are p r e s e n t l y d i f f i c u l t to express i n ALCHEM. For example, the chemist f a i r l y e a s i l y p e r c e i v e s the e f f e c t of h e t e r o c y c l i c f u n c t i o n a l i t y remote from a r e a c t i o n center, but ALCHEM statements to accomplish such p e r c e p t i o n are q u i t e complex. Besides being l e s s e a s i l y comprehended, complex ALCHEM statements g e n e r a l l y r e q u i r e extensive t e s t i n g to v e r i f y that they are i n t e r p r e t e d by the program as intended. We expect that f u r t h e r development of the ALCHEM vocabulary w i l l make the language even more powerful and flexible. Conclusion I f a convenient, r o u t i n e l y u s e f u l s y n t h e t i c a n a l y s i s p r o gram i s developed, i t w i l l be accepted. Although many chemists r e s i s t e d IR, NMR and mass s p e c t r a l techniques when they were introduced, no modern chemist would dream of performing s t r u c ture determination e x c l u s i v e l y by degradation experiments. Complex organic s y n t h e s i s i s d i f f i c u l t , and the chemist can use h e l p . I f computer aided planning can reduce the number of u n s u c c e s s f u l experiments run, research managers w i l l embrace the methodology· Merck i s p a r t i c i p a t i n g i n development of the SECS software i n order to gain experience i n t h i s area; i n order to help assure that the program develops i n t o a u s e f u l t o o l f o r pharmac e u t i c a l research; and f o r what i t can c o n t r i b u t e to Merck's s y n t h e t i c e f f o r t , even at t h i s e a r l y stage. Development of a s y n t h e s i s may more or l e s s be d i v i d e d i n t o the " s y n t h e t i c p l a n n i n g " stage, where a rough s y n t h e t i c approach i s blocked out, and a " r e a c t i o n r e t r i e v a l " stage, where analogous sequences and s p e c i f i c r e a c t i o n c o n d i t i o n s are sought. An optimal " s y n t h e t i c p l a n n i n g " t o o l i s probably not best f o r the " r e a c t i o n r e t r i e v a l " f u n c t i o n S E C S i s p r i m a r i l y a "synt h e t i c p l a n n i n g " t o o l . There i s a r e a l need f o r " r e a c t i o n r e t r i e v a l " a i d s , but we suspect that t h i s w i l l have to be met p r i m a r i l y by other systems. Perhaps the new Derwent Reaction R e t r i e v a l Service w i l l f i l l t h i s need.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

24.

GUND E T A L .

The

Merck

Experience

549

SECS program improvements must occur i n s e v e r a l areas. We hope to implement an up-to-date v e r s i o n of SECS at Merck, to overcome many present l i m i t a t i o n s . In a d d i t i o n , h i g h - l e v e l s t r a t e g i e s must be developed to guide analyses, e s p e c i a l l y as the r e a c t i o n data base expands, i n order to remove u n i n t e r e s t i n g precursors and keep to a reasonable s i z e the t o t a l number of s t r u c t u r e s generated. While our experience may help d e f i n e s u c c e s s f u l s t r a t e g i e s , t h i s i s not the area of Merck's i n i t i a l interest· Merck's main emphasis at present i s i n b u i l d i n g an improved r e a c t i o n data base. Already i t i s c l e a r to us that t h i s must be done slowly and c a r e f u l l y , by expert chemists, with c o n t i n u a l refinement of transforms based on experience. The t o t a l number of s y n t h e t i c r e a c t i o n s i s r a t h e r l a r g e , and i t i s not at a l l c l e a r that one company can commit enough resources to cover much of s y n t h e t i c chemistry i n a reasonable time p e r i o d . Some s o r t of exchange of transforms by p a r t i c i p a t i n g companies, such as i s c u r r e n t l y underway i n Europe,Ê2)would c o n s i d e r a b l y speed system development. Acknowledgement We are g r a t e f u l to M. J . Pensak f o r h i s c o n t r i b u t i o n s to an improved molecule input r o u t i n e and the hard copy summary p r o gram; to Dr. Dale R. Hoff f o r h i s c a r e f u l a n a l y s i s of system c a p a b i l i t i e s and f o r h i s c o n t i n u i n g e f f o r t s to improve the r e a c t i o n data base; to the many Merck chemists who p a r t i c i p a t e d i n e v a l u a t i n g and improving the program; and to s e v e r a l f a r sighted a d m i n i s t r a t o r s who i n i t i a t e d t h i s p r o j e c t and sustained i t i n i t s e a r l y stages. SECS program development at Santa Cruz has been supported by the N a t i o n a l I n s t i t u t e s of Health, Research Resources Grant No. RR-01059, and through computer support from the Stanford U n i v e r s i t y SUMEX-AIM P r o j e c t Grant No. RR-00785.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

550

COMPUTER-ASSISTED DRUG DESIGN

Literature Cited 1. 2. 3. 4. 5.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

6.

7.

8. 9. 10.

11.

12. 13. 14.

15.

Corey, E. J. and Wipke, W. T., Science (1969) 166, 178. Review: Bersohn, M. and Esacks Α., Chem. Revs. (1976) 76, 269. Review: Gund, P., Ann. Repts. Med. Chem. (1977) 12, 288. Symposium: Computer-Assisted Organic Synthesis, W. T. Wipke and W. J . Howe, Edits., ACS Symposium Series, No. 61, 1977. Sarett, L. H., unpublished speech before Synthetic Organic Chemical Manufacturers Association, June 1964; quoted in Ref. 6. Wipke, W. T., "Computer Representation and Manipulation of Chemical Information", W. T. Wipke, S. R. Heller, R. J . Feldmann and E. Hyde, Edits., J . Wiley, New York, p. 147, 1974. Gund, P., Andose, J . D. and Rhodes, J . B. in Contributed Papers to III Internat. Conf. on Computers in Chemical Res., Educ. & Technol., Ε. V. Ludeña and F. Brito, Edits., Centro de Estudios Avanzados del,Instituto Venezolano de Investigaciones Cientificas (IVIC), Caracas, p. 226, 1977. Review: Wipke, W. T., Braun, H., Smith, G., Choplin, F. and Sieber, W. in Ref. 4, p. 97. Different releases of the SECS program are identified by different version numbers, starting with 1.0. The current release of the program corresponds to version 2.7. "Utilization of Stereochemistry and Other Aspects of Computer-Assisted Synthetic Design", T. M. Dyoth, Ph.D. Thesis, Princeton University, 1973 (University Microfilms, No. 74-9677). Our current computer environment consists of an IBM 370/168 computer running under the OS/VS2 MVS-3.7A operating system. We have also run SECS on TSO under the OS-MFT and OS-MVT operating systems. Initially available through First Data Corporation, Waltham, Massachusetts, the program is now available on ADP Network Services, Inc., Ann Arbor, Michigan. Kerneghan, B. W. and Plauger, P. J., "Software Tools", Addison-Wesley, Reading, Massachusetts, 1976. At Merck, we are using DEC GT-42 and GT-43 graphics display terminals with 16 Κ words of core memory. Communication with our host computer11 is at 1200 baud using VADIC 3400 series modems. Detailed instructions for this modification to the operating system were already available to us through purchase of the PLOT-10 Terminal Control System software from Tektronix, Inc., for support of Tektronix 4010 series terminals on IBM computers.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

24.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch024

16·

17. 18. 19. 20.

21.

22. 23. 24. 25. 26. 27. 28. 29.

GUND ET AL.

The Merck Experience

551

DEC uses a full-duplex communications protocol with XON/XOFF control over transmission in both directions. "Full duplex" permits simultaneous transmission and reception of data. "XON/XOFF" control means that either host computer or terminal can turn off transmission from the other device by sending an "XOFF" control character, and can request resumption of transmission by sending an "XON" control character. By contrast, IBM uses a half-duplex communications protocol with the host computer the master and the terminal the slave device. When the host computer is transmitting data, it cannot receive, and when receiving, it cannot send (without loss of data). To prevent line conflict, the host computer invites the terminal to send data by transmitting a special character sequence. The terminal must wait until receiving this "invitation" before sending data to the host. Reprogramming of GT42LIB was performed on a contract basis by William S. Price Associates, Inc., New York, New York. Beebe, N. H. F. in Quantum Chemistry Program Exchange Newsletter No. 63, Indiana University (November, 1978), p. 5. American National Standards Institute. American National Standard Programming Language FORTRAN, X3.9-1966. American National Standard Programming Language FORTRAN, X3.9-1978; see also, W. Brainerd, Ed., Comm. ACM, 21, 806 (1978) and "FORTRAN 77", H. Katzan, Jr., Van Nostrand Reinhold, New York, New York, 1978. Dominy, B., "SECS and the Information Scientist", presented at the Science Information Subsection of the Pharmaceutical Manufacturer's Association Meeting, Washington, D.C., March 6, 1977. Corey, E. J., Howe, W. J., Orf, H. W., Pensak, D. A. and Petersson, G., J . Amer. Chem. Soc. (1975) 97, 6116 (1975). Shuman, R. F., Pines, S. H., Shearin, W. E . , Czaja, R. F., Abramson, N. L. and Tull, P., J. Org. Chem. (1977) 42, 1914. Pines, S. H., Czaja, R. F. and Abramson, N. L . , J . Org. Chem. (1975) 40, 1920. Ten Broeke, J., Douglas, A. W. and Grabowski, E. J. J., J . Org. Chem. (1976) 41, 3159. We are indebted to Professor Magnus for his permission to use this example. Bruns, H., private communication. Gund, P., Andose, J . D. and Rhodes, J. B., in Ref. 4, p. 179. Bruns, H., Textes Conf. Cadre Congr. Int. "Contrib. Calc. Electron Dev. Genie Chim. Ind.", A, Soc. Chim Ind., Paris, 1978, p. 83.

RECEIVED

June 8, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

25 A Hierarchal QSAR Molecular Structure Calculator Applied to a Carcinogenic Nitrosamine Data Base B. PETIT, R. POTENZONE, JR., and A. J. HOPFINGER—Department of Macromolecular Science, Case Western Reserve University, Cleveland,OH 44106

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

G. KLOPMAN—Department of Chemistry, Case Western Reserve University, Cleveland, OH 44106 M. SHAPIRO—Division of Computer Research and Technology, National Institutes of Health, Bethesda, MD 20014 Lijinsky and coworkers (1) have reported a data base contain­ ing two quantitative measures of carcinogenic potency for a set of nitrosamines. The first carcinogenic measure, TD50, is the average time, in weeks, for 50% of a set of Sprague-Dawley rats to die relative to a control set of equal population. An upper limit of 100 weeks has been placed on each experiment. The second measure is an overall assessment of relative carcinogen­ icity, RC, based upon observations made over the course of the experiments. RC is recorded on a discrete scale of 0 to 4 with zero being "noncarcinogenic" and four being "extremely carcino­ genic". Exposure to the nitrosamine was achieved by placing a fixed dosage in the animal's drinking water. The sites of tumor forma­ tion were recorded for each compound tested. For specific test­ ing details see Lijinsky and Taylor reports 2-4. It is to be emphasized that this data base was not constructed from biological experiments designed for quantitative structure activity relation­ ship, QSAR, studies. The experiments were developed only to a s c e r t a i n whether or not a compound i s " c a r c i n o g e n i c " . Con­ sequently, r e l a t i v e l y high doses have been used which l e a d t o a narrow range o f responses. Nevertheless, Singer e t a l . CD and Wishnok e t a l . (6) have used b i o l o g i c a l a c t i v i t i e s of the type and q u a l i t y as T D 5 0 to e s t a b l i s h QSAR's f o r some s e t s of nitrosamines. Singer e t a l . (5) found a l i n e a r c o r r e l a t i o n between experimentally measured water/ o c t a n o l p a r t i t i o n c o e f f i c i e n t , P, and the percentage of SpragueDawley r a t s b e a r i n g o l f a c t o r y carcinomas induced by s u b s t i t u t e d N-nitrosopiperidines. In a d d i t i o n , a p a r a b o l i c c o r r e l a t i o n was e s t a b l i s h e d between Ρ and the r e l a t i v e mean l i f e t i m e of the animals b e a r i n g h e p a t o c e l l u l a r carcinomas induced by a s m a l l , but moderately d i v e r s e , set of n i t r o s a m i n e s . Wishnok e t a l . (6) have found the water/hexane p a r t i t i o n c o e f f i c i e n t P and " e l e c t r o n i c f a c t o r s " as measured by T a f t σ* to c o r r e l a t e with c a r c i n o g e n i c a c t i v i t y f o r a s e r i e s of n i t r o s o f

0-8412-0521-3/79/47-112-553$07.25/0 © 1979 A m e r i c a n C h e m i c a l Society

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

554

COMPUTER-ASSISTED DRUG DESIGN

compounds. However, the a p p l i c a b i l i t y of σ* t o n i t r o s o group s u b s t i t u e n t s i s q u e s t i o n a b l e . Nevertheless, both groups of researchers concluded t h a t t r a n s p o r t o f the carcinogen to the a c t i v e s i t e , as i s assumed modeled through p a r t i t i o n c o e f f i c i e n t , p l a y s a s i g n i f i c a n t r o l e i n s p e c i f y i n g c a r c i n o g e n i c potency. We have c a r r i e d out a s e r i e s of i n v e s t i g a t i o n s i n p u r s u i t of a QSAR f o r a s e t of c y c l i c nitrosamines from the L i j i n s k y data base ( 1 ) . T D 5 0 has been used as the b i o l o g i c a l measure. A l l the c y c l i c nitrosamines considered produced tumors o f the esophagus. In s e v e r a l i n s t a n c e s tumors were found a t a d d i t i o n a l s i t e s i n the animals. I t i s to be emphasized that the occurrence of tumors, and the reduced average l i f e of the animals, due to exposure to nitrosamines, must be assumed i n d i c a t i v e of the c a r c i n o g e n i c potency o f a compound. Our nitrosamine QSAR i n v e s t i g a t i o n s can be c l a s s i f i e d i n terms o f four i n c r e a s i n g l e v e l s of s t r u c t u r a l s o p h i s c a t i o n ; 1. determination of group-additive Q ) molecular d e s c r i p t o r s , 2. c a l c u l a t i o n of d e s c r i p t o r s using molecular mechanics methods (8), 3. c a l c u l a t i o n o f quantum mechanical (molecular o r b i t a l ) (9) d e s c r i p t o r s , and 4. mechanism of a c t i o n computations which employ a l l of the above mentioned d e s c r i p t o r s . In general QSAR models can be constructed from any combina­ t i o n of the four l e v e l s o f s t r u c t u r e c a l c u l a t i o n . We are c u r r e n t l y developing a software package to compute the d i f f e r e n t c l a s s e s of molecular d e s c r i p t o r s and to c o n s t r u c t a c t i o n models. This software package i s being c a l l e d "A H i e r a r c h a l QSAR Molecular S t r u c t u r e C a l c u l a t o r " . Method 1. Group A d d i t i v e Molecular D e s c r i p t o r s ; Log Ρ values were c a l c u l a t e d u s i n g Rekker fragment constants ( 1 0 ) a p p l y i n g nona d d i t i v e c o r r e c t i o n s according to Leo ( H ) . Fragment constants are not a v a i l a b l e f o r the n i t r o s o group. To estimate t h i s f r a g ­ ment constant, f(NNO), the c y c l i c nitrosamines were grouped according to the types of atoms i n the r i n g . Those compounds c o n t a i n i n g only a l i p h a t i c u n i t s , besides a s i n g l e n i t r o s o group, were grouped together as were the nitrosomorpholines, the n i t r o p i p e r a z i n e s , and d i - N - n i t r o s o - d e r i v a t i v e s . In c o n s t r u c t i n g these c l u s t e r s we assume that the e l e c t r o n i c p r o p e r t i e s of the n i t r o s o group are a l t e r e d by i n - r i n g s u b s t i t u e n t s . In t u r n , changes i n the e l e c t r o n i c p r o p e r t i e s o f the n i t r o s o group a l t e r s i t s o l u t e s o l v e n t behavior and, consequently, l o g P. A l i n e a r l e a s t square f i t of the experimental l o g Ρ versus the c a l c u l a t e d l o g Ρ (not c o n t a i n i n g a c o n t r i b u t i o n from the n i t r o s o group) has been c a r r i e d out f o r each o f these four groups. The negative of the l o g Peal i n t e r c e p t o f the l e a s t - s q u a r e f i t l i n e can be i d e n t i f i e d as f(NNO). The legend o f Table 1 contains the f(NNO) of each

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

25.

PETIT E T A L .

Q S A R Molecular

Structure

555

Calculator

of the f o u r compound groups. The experimental l o g Ρ are reported by Singer e t a l . (5) and were measured by o p t i c a l d e n s i t y spectroscopy. We have c a r r i e d out a l i n e a r r e g r e s s i o n a n a l y s i s between l o g Pexp and l o g P e a l f o r the complete data base i n Table 1. The c o r r e l a t i o n equation is log P

e x p

= 1.0049 l o g P

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

Ν = 28

R = .97

c a l

+ .0108

S = ±

(1)

.203

where Ν i s the number of compounds, R i s the c o r r e l a t i o n c o e f f i ­ c i e n t , and S the standard d e v i a t i o n . Log P, at a f i x e d temperature, i s a measure of the f r e e energy d i f f e r e n c e between a s o l u t e i n water and 1-octanol. At room temperature, Ρ =

log

.735

(PH O -

F

2

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).

(2)

Eq. (2) i n d i c a t e s that F H ° and F can both vary, while l o g Ρ remains constant. Consequently, i f the chemical a c t i v i t y ( s o l u t i o n f r e e energy) of a compound i n the aqueous and/or l i p i d medium i s a s i g n i f i c a n t f e a t u r e ( s ) i n c o n t r o l l i n g b i o l o g i c a l a c t i v i t y , l o g Ρ may not be an adequate descriptor. Fortu­ n a t e l y , a l a r g e number of aqueous a c t i v i t y c o e f f i c i e n t s of organic compounds have been measured (12). Using a group a d d i t i v e formalism and the thermodynamic r e l a t i o n s h i p , 2

aH 0 2

= exp(-F o/RT) H2

o c t

(3)

i t has been p o s s i b l e to construct a s e t of aqueous f r e e energy fragment constants analogous t o Rekker f-constants (10) and Hansch π-constants (13). U20 i s the measured aqueous a c t i v i t y coefficient. The corresponding aqueous f r e e energy fragment constants, w(X), are l i s t e d i n Table 2. No w(NN0) constants were a v a i l a b l e from the a n a l y s i s of the aqueous a c t i v i t y c o e f f i c i e n t . Consequently, we c a r r i e d out computer s i m u l a t i o n c a l c u l a t i o n s to model the i n t e r a c t i o n of water molecules with an NNO group. These s i m u l a t i o n s t u d i e s are i d e n t i c a l to those employed to estimate the aqueous and 1-octanol f r e e energies of some simple o r g a n i c com­ pounds (14). I n t e r e s t i n g l y , these c a l c u l a t i o n s suggest that the o c t a n o l c o n t r i b u t i o n to l o g Ρ f o r the NNO group i s e s s e n t i a l l y zero. The e l e c t r o s t a t i c i n t e r a c t i o n s between the water molecules and NNO dominate i n the s o l v a t i o n e n e r g e t i c s . The set of molecular aqueous f r e e energies of the c y c l i c n i t r o ­ samines are i n Table 1. Eq. (2) can be s o l v e d f o r F and these d e s c r i p t o r values f o r each of the c y c l i c nitrosamines are a l s o reported i n Table 1. a

o c t

2. Molecular Mechanics D e s c r i p t o r s : A c o n s i s t e n t f o r c e f i e l d (CFF) method, adapted from the MMI program of A l l i n g e r , ( ϋ ) of

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

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Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

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In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

25.

557

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υ

υ

χ

J

-

b.

υ

1

r>.

CM

sr

oo

en

m

«·

oÔ

M

g-

26.93

Ax-Ax

42.41

CM ©A

•

ï

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

[70.92]

(37.45)

Table 1 (2 o f 5)

OA « CM

en

00

O

m

1

m i-t tfi .

Γ«·

© «*· —

chai

boat


162. ί

-64.7

OH

139.0

OH

ΔΕ(ΙΙ-ΙΙΙ)

(227.5)

(18.4)

OH

OH

-68.0

ΔΕ(ΙΙ-Ι)

137.3

(207.0)

(1.7)

129.5

(224.9)

(38.7)

155.8

(224.7)

(17.2)

158.3

(226.7)

(14.9)

144.0

(226.8)

(18.7)

(224.1)

(36.0)

(224-4)

(13.4)

OH

OH

VJ) -56.7 /

168.2

OH

OH OH

^

-51.7

J

173.0

OH

173.2

-53.5

OH

OH

OH

OH

OH

-44.3

OH

> λ* (

OH

OH

OH

179.8

0H

"(fol"».6

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

25.

567

ÇSAR Molecular Structure Calculator

PETIT E T A L .

Table 3 I HO y

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

c

Ε

II

Ε

III

Ε

Δε(ΙΙ-Ι)

Δε(ΙΙ-ΙΙΙ)

-101.8

128.9

81.7

(230.7)

(47.2)

98.4

131.3

111.5

(229.7)

(19.8)

144.8

(231.4)

(16.7)

130.0

(237.1)

(30.9)

142.6

(233.7)

(15.9)

(230.2)

(18.41

(189.2)

(14.8

OH

HO

HO

OH

Cr^-69.9 Cjr

OH

H^~3H

OH

^TL

1615

3>

CA

-ς

160.9

OH

OH

OH

ICJI OH

OH

OH

|^168.

61.6

Φ H3C-CH2CJI

-25,

OH

OH

OH

H C-CH Cil 2

|H C-®C* 3

2 0 0 e 0

2

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG

568

The g e n e r a l i z a t i o n introduced i n t o eq. ( 4 ) i s F i s d e f i n e d as: _F

DESIGN

which

i s the f r a c t i o n of molecules reaching the c r i t i c a l s i t e which have been transformed i n t o an a c t i v e m e t a b o l i t e .

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

Generally, F has been s e t equal to one, that i s e x p l i c i t metabolic c o n s i d e r a t i o n s have been neglected. In t u r n , K, which accounts f o r drug-target i n t e r a c t i o n s i s d e f i n e d i n our formalism as: Κ i s the a c t i v i t y of the metabolite, i . e . i t s r e a c t i v i t y toward the t a r g e t molecule. We f u r t h e r note that s e v e r a l metabolites are allowed i n the p o s t u l a t e d metabolic pathway of F i g . 2. Therefore, eq. (4) becomes: d(response) dt

_ ACSF.K.

(5)

. 1 1

ι where 1 r e f e r s to the i * * * metabolite and the c o n s t r a i n t ΣΈ± = 1 i s present. Eq. (5) can be solved under three d i f f e r e n t b i o l o g i c a l boundary c o n d i t i o n s : 1

1

1. 2. 3.

Concentration and time are constant, Concentration and response are constant, Response and time are constant.

and

The T D ^ Q and RC measures f a l l i n t o the second c l a s s i f i c a t i o n . Consequently, the f i n a l form of the drug a c t i o n equation becomes

ϊ " Ψ Α

( 6 )

An expression f o r K. was formulated i n terms of a product of s t r u c t u r a l switches:

K

±

=TTs

ui

, where

i n which X . = 1 or 0 depending upon the presence of d e s c r i p t o r u i n metabolite i .

(7)

or absence

V . measures the importance of d e s c r i p t o r u i n metabo­ l i t e i i n the production of the observed response. The d e s c r i p t o r s employed i n c l u d e those given i n Tables 1 and 3. A i n eq. (6) was s e p a r a t e l y considered as represented by a guassian f u n c t i o n i n l o g Ρ m u l t i p l i e d by the p o p u l a t i o n of the boat conformer. The parent compound was used to determine the values of Log Ρ i n A. Our program MULFIT which i s a form of non-

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

25.

PETIT E T AL.

ÇSAR

Molecular

Structure

Calculator

569

l i n e a r r e g r e s s i o n a n a l y s i s was used to determine the c o e f f i c i e n t s f o r the A term, the V i and the Έ ± . The values of the F^, i n turn, provide the information to determine which metabolic species are most important i n the a c t i o n model. The V ± i n d i c a t e which molecular d e s c r i p t o r s are most important i n the a c t i o n of a p a r t i c u l a r metabolite. u

U

Results

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

Two d i s t i n c t types of s t r u c t u r e a c t i v i t y r e l a t i o n s h i p s were c a r r i e d out; one independent of the a c t i o n model, the other based upon the proposed mechanism of a c t i o n . 1.

QSAR-Independent of

an A c t i o n Model:

The T D 5 0 were i n i t i a l l y c o r r e l a t e d against the complete sets of group a d d i t i v e molecular f e a t u r e s , CFF a b s o l u t e conformer energies, and e q u i v a l e n t atom r e s i d u a l charge d e n s i t i e s using l i n e a r r e g r e s s i o n a n a l y s i s . Both l i n e a r and quadratic values were considered f o r each d e s c r i p t o r . The systematic and r e p e t i t i v e d e l e t i o n of a s i n g l e d e s c r i p t o r term from the general c o r r e l a t i o n equation i n d i c a t e d that a l l CFF conformer energies and atomic charge d e n s i t i e s , except f o r those of the C , d i d not c o n t r i b u t e meaningfully to the c o r r e l a t i o n equation. A d d i t i o n a l molecular mechanics d e s c r i p t o r s were constructed by t a k i n g a l l combinations of energy d i f f e r e n c e s between the d i f f e r e n t conformer s t a t e s considered. Several degeneracies arose because of the energy equivalence of some conformers f o r c e r t a i n compounds. Nevertheless some of the sets of energy d i f f e r e n c e s enhanced the c o r r e l a t i o n when both l i n e a r and quad­ r a t i c values were i n c l u d e d i n the r e g r e s s i o n a n a l y s i s . The d e s c r i p t o r s e t s of energy d i f f e r e n c e s are h i g h l y c o l i n e a r with respect to c o r r e l a t i o n with TD50. Consequently, we sought the one set of energy d i f f e r e n c e s which maximized the s i g n i f i c a n c e of the c o r r e l a t i o n . The energy d i f f e r e n c e between the most s t a b l e boat and most s t a b l e c h a i r form of each compound y i e l d e d the highest c o r r e l a t i o n . These energy d i f f e r e n c e s , ΔΕ, are reported i n Table 1. I t should be noted that these ΔΕ may, i n p a r t at l e a s t , c o r r e l a t e best with TD50 because t h i s data set contains the l e a s t degeneracy ( l a r g e s t number of unique e n t r i e s ) . When the ΔΕ are included i n the c o r r e l a t i o n a n a l y s i s , the atomic charge d e n s i t i e s of the C no longer are s i g n i f i c a n t . This suggests that the c o n t r i b u t i o n of the C charge d e n s i t i e s to the c o r r e l a t i o n are included w i t h i n the ΔΕ. This i s c o n s i s t e n t with the f a c t that the charge d e n s i t i e s are used to determine the CFF energies. If t h i s i s the case, then the C atomic charge d e n s i t i e s do not c o n t r i b u t e to the T D 5 0 c o r r e l a t i o n through chemical r e a c t i v i t y (an i n t e r m o l e c u l a r process), but through conformer s t a b i l i t y (an i n t r a m o l e c u l a r process). a

a

a

a

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

570

A l l combinations of l i n e a r and q u a d r a t i c values of the r e ­ maining d e s c r i p t o r s were used i n l i n e a r r e g r e s s i o n f i t s to the T TD50. ^[ie roost s i g n i f i c a n t c o r r e l a t i o n equation found i s , TD50 = 97.7

+ 29.7

+ 1.23 Ν - 22

(ΔΕ)

(F

) + 3.8

o c t

(F

) 2 - 6.61

o c t

(ΔΕ)

2

(9)

R = .92

S = ί

8.4

Eq. (9) has been judged s i g n i f i c a n t because the constant term (97.7) i s a t the upper end of the TD50 a c t i v i t y range [0,100]. C o n t r i b u t i o n s of F and ΔΕ from compounds i n the data base to eq. (9) must be to lower TD50. T h i s cannot occur r a n ­ domly as compared to the case where the constant term i s 50, and "random f l u c t u a t i o n " c o n t r i b u t i o n s from F t and ΔΕ to reproduce the range of TD50, [0,100]. The number of d e s c r i p t o r terms i n eq. ( 9 ) , f o u r , two p a i r s of i n t e r f u n c t i o n a l d e s c r i p t o r s , i s small with respect to the number of o b s e r v a t i o n s , 22. There i s a "rule-of-thumb" that the r a t i o of observations to d e s c r i p t o r terms must be f o u r , or more, to y i e l d a s t a t i s t i c a l l y s i g n i f i c a n t r e l a t i o n s h i p . Thus t h i s i s a d d i t i o n a l evidence i n support of the s t a t i s t i c a l v a l i d i t y of eq. (9). Each of the two d e s c r i p t o r s F and ΔΕ appear i n the c o r r e l a t i o n equation (eq. 9) with p a r a b o l i c dependence. This means that each d e s c r i p t o r possesses an optimum value which y i e l d s a maximum, or minimum, c o n t r i b u t i o n to determining Τϋ50· These optimum values can be determined by simple p a r t i a l d i f f e r e n t i a t i o n of eq. ( 9 ) ,

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

o c t

o c

o c t

8TD D U a F

~ 29.747.6 (Foct) - 0

oct F

3

( oct>opt = ~ -

9

kcal/mole

(10)

Many c y c l i c nitrosamines possess F v a l u e s both l e s s than, and greater than, -3.9 kcal/mole (see Table 1). Thus the com­ pound data base used to c o n s t r u c t eq. (9) samples a s i g n i f i c a n t range of F - s p a c e with r e s p e c t to TD50. o c t

o c t

Eq. (3) y i e l d s a ( A E ) t of o p

ΔΤΌ D U

8(ΔΕ)

= -6.6 (AE)

+ 2.46 o p t

(ΔΕ) = 0

= 2.69

kcal/mole

(11)

The ( A E ) p t = 2.69 kcal/mole i s a l s o l o c a t e d near the middle of (ΔΕ)-space f o r the range of (ΔΕ) values i n the compound data s e t . Thus the p a r a b o l i c TD50 dependence on (ΔΕ) i s a l s o judged significant. We d i d not s e t a s i d e some compounds to use as " t e s t s " of the QSAR s i n c e the s i z e of the data base i s s m a l l . However, there are 0

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

25.

PETIT E T

AL.

QSAR Molecular Structure Calculator

571

eleven compounds i n Table 1 which have TD50>100. These com­ pounds could not be used i n c o n s t r u c t i n g eq. ( 9 ) . However, we can use these compounds to q u a l i t a t i v e l y t e s t (at l e a s t i n terms of extending the range o f ) e q . ( 9 ) by p r e d i c t i n g T D 5 0 . The pre­ d i c t e d T D 5 0 of the eleven compounds have observed TD50 s>100 are l i s t e d i n Table 4. Only two compounds, 2-carboxy-nitros o p y r r o l i d i n e and 2,3,5,6 t e t r a m e t h y l d i n i t r o s o p i p e r a z i n e , are p r e d i c t e d to have TDso's considerably l e s s than 100. The 2carboxy compound, as w e l l as a l l the c a r b o x y l - c o n t a i n i n g com­ pounds, w i l l be p r e d i c t e d , from eq. ( 9 ) , to have higher TT^o's i f the charged form of the c a r b o x y l group i s assumed. The poor p r e d i c t i o n of TD50 f o r 2,3,5,6 t e t r a m e t h y l d i n i t r o s o p i p e r a z i n e might be due to the wrong s e l e c t i o n of the molecular c o n f i g u r a t i o n . I f , f o r example, the a l l - e q u a t o r i a l c o n f i g u r a t i o n were s e l e c t e d , ΔΕ i s estimated to be near 10 which would lead to a p r e d i c t e d TD50 of about 110. We r e i t e r a t e that we do not have knowledge of the e x p e r i ­ mental c o n f i g u r a t i o n a l s t a t e s , or the extent of c a r b o x y l i o n ­ i z a t i o n , of the c y c l i c nitrosoamines. The s e l f - c o n s i s t e n c y of the QSAR i s the only i n d i r e c t evidence f o r p r e d i c t i n g con­ f i g u r a t i o n a l , conformer, and i o n i z a t i o n s t a t e s of the molecules. L i n e a r r e g r e s s i o n a n a l y s i s has p i t f a l l s . There i s always the p o s s i b i l i t y of chance c o r r e l a t i o n s . Hence, we opted to analyze the data using an a l t e r n a t e s t a t i s t i c a l method, namely c l u s t e r a n a l y s i s . The data were s c a l e d so that each of the d e s c r i p t o r s ranged i n value between 0 and 1. Minimal tree spanning methods was employed i n the determination of c l u s t e r s (24). We d i d make use of some g u i d e l i n e s e s t a b l i s h e d i n the l i n e a r r e g r e s s i o n study: Only the four most s i g n i f i c a n t d e s c r i p t o r s ( oct> H20 ΔΕ, and Log P) were used i n the c l u s t e r a n a l y s i s . The r e s u l t s are shown i n F i g . 3. T h i s i s a n o n - l i n e a r map of the d e s c r i p t o r s i n t h e i r four-dimensional space p r o j e c t e d i n t o twodimensions. Nine d i f f e r e n t c l u s t e r s can be i d e n t i f i e d . However, one c l u s t e r plus one member of a nearby c l u s t e r (the enclosed area w i t h i n the map) contains a l l a c t i v e compounds except f o r the 3-hydroxy n i t r o s o - p i p e r i d i n e . That i s , h i g h l y c a r c i n o g e n i c com­ pounds c l u s t e r together while the "non-carcinogenic" cyclic nitrosamines are s c a t t e r e d about i n the four-dimensional d e s c r i p t o r space. The values of the four d e s c r i p t o r s were a l s o p a i r w i s e c o r r e l a t e d against one another. In a d d i t i o n , the s i n g l e v a r i a b l e (no t e s t i n g f o r the e f f e c t of combinations) p r e d i c t i n g a b i l i t y was measured by p u t t i n g the data i n t o c a t e g o r i e s , based upon t h e i r TD50 value being l e s s than, or greater than, 75. The F i s h e r ranking method was then a p p l i e d to the data base. The r e s u l t s are given i n Table 5. Table 5a i n d i c a t e s that H20 and Log Ρ are h i g h l y c o r r e l a t e d (.76) as w e l l as F and H20 (.88). I n t e r e s t i n g l y , however, F and Log Ρ are much l e s s c o r r e l a t e d (.35). Table 5b i n d i c a t e s that F i s the most

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

,

F

F

9

F

F

o c t

o c t

o c t

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED

572

DRUG DESIGN

Table 4

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

P r e d i c t e d T D - Q f o r compounds possessing observed TD > 100 u s i n g eq. (9). Compound

P r e d i c t e d TD^^

Nitrosopiperidines 2,6 Dimethyl 2,2,6,6, Tetramethyl 4-t-Butyl 2-Carboxyl 4-Carboxyl -

105.9 99.6 257.2 85.7 98.9

Nitrosopyrrolidines 2,5 Dimethyl 2-Carboxy 2-Carboxy - 4-hydroxy

145.7 37.3 (120.2) 139.2

Nitrosopiperazines Nitrosopiperazine 4-Methyl 2,3,5,6 Tetramethyldinitrosopiperazine

85.0 100.0 35.2

b

D

a)

the c a r b o x y l group i s charged.

b)

the low T D , _ Q i s probably i n d i c a t i v e of s e l e c t i n g the wrong c o n f i g u r a t i o n ( s ) and/or conformer s t a t e s .

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

a

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

PETIT E T A L .

QSAR

Molecular

Structure

Calculator

573

90

101 101

101 101

101

Figure 3. 'Nonlinear map of the location (the numbers) of the cyclic nitrosamines in (ΔΕ, Log P, F o, F )-space as determined by cluster analysis. The numbers correspond to the experimental TD in weeks. H2

oct

50

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

574

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

Table 5 C o r r e l a t i o n Table of Log P, F H O > oct>

a)

Log Ρ Log Ρ F

F

9

H

F

Foct

H 2 0

a

n

d

Δ Ε β

ΔΕ

1

0

.76

1

.35

.88

1

.12

.24

.26

2 F oct ΔΕ

b)

S i n gle V a r i a b l e P r e d i c t i v e Capacity of Log > H20» oct> · p

Variable

F

1

v

F

F

F

a

n

d

Δ Ε

Unnormalized P r e d i c t i v e Weight 2.24 1.19

oct .07 ΔΕ Log Ρ

.009

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

25.

PETIT E T A L .

Q S A R Molecular

Structure

Calculator

575

F

important p r e d i c t i v e d e s c r i p t o r followed by H 0 . ^ P, i n d i v i d u a l l y , are of very l i t t l e p r e d i c t i v e v a l u e . This f i n d ­ i n g , i n conjunction with eq. (9), suggests that F t i n eq. (9) i s the dominate p r e d i c t i v e d e s c r i p t o r and ΔΕ only becomes important i n those few cases where F s p r e d i c t i v e capacity fails. 2

o c

f

o c t

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

2.

QSAR-Using an A c t i o n Model

The set of equations (6-8) employing combinations of molecu­ l a r d e s c r i p t o r s from Table 1 and the d e s c r i p t o r s from Table 3 were used to d e s c r i b e the a c t i o n model. The optimum a c t i o n model achieved to date f o r the nitrosamines l i s t e d i n Table 6 i s ,

^ 1U

= A C F i P i + F P ) where, 2

(12)

2

50

100 i s an a r b i t r a r y s c a l i n g constant chosen equal to the maximum time d u r a t i o n of the experiments, and A = (8.34

2

expf*05(Log Ρ - 1 . 3 2 ) ] ) ( 1 + exp(-.26

1

ΔΕ))" .

The f r a c t i o n of each metabolite reaching the t a r g e t chosen to be uniform, e.g. Έ ± = (set) = F = (set) =«5. we have assumed a n o n - s e l e c t i v e o x i d i z i n g agent (P-450?) s e t t i n g equal weights to the two metabolic pathways (see P i and P are the switch v a r i a b l e products d e f i n e d as; 2

site is That i s , in F i g . 2).

2

P i -jÏ!

( 1 - V j l X j l ) and,

p

( " " j l j 2 ^ where, l a s t l y ,

x

l l X 2 1

x

31

X X

1

2

4 1

51

o r

x

12 or X

=

2 2

o r

x

v

x

C-C Φ i s formed, e l s e = 0. = 1 i f ( C ) - C - C ® , f o r n_>l, i s formed, e l s e =

1

i f

n

C

C

32 = 1 if c' ~ ^

i s formed

>

e l s e =

°·

or X 4 2 = 1 i f C - C - C ® - C i s formed, e l s e « o r

x

o r

X

52

=

1

i f

=

1

i f

X

0.

0.

> C - C ® (X=halogen) i s formed, e l s e =

0.

*61 62 C = C - C © i s formed, e l s e = 0. The assignment of the Xjj[ were made from an a n a l y s i s of the ΔΕ values given i n Table 3 f o r the model m e t a b o l i t e s . The r e s u l t i n g n o n l i n e a r r e g r e s s i o n f i t of the V j ^ are V - Q = 0.50, V i - .438, V = .484, V = 1.000, V = .021, V = -0.007. Figure 4 i s a p l o t of p r e d i c t e d T D 5 0 , using eq. (12), versus the observed T D 5 0 . The major o u t l y e r i s 4 - k e t o - n i t r o s o p i p e r i d i n e . It i s not p o s s i b l e to compute a c o r r e l a t i o n c o e f f i c i e n t f o r t h i s f i t t i n g procedure since n o n l i n e a r r e g r e s s i o n methods have been employed. 2

3 1

4 1

5 1

6 1

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

Table 6

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

Nitrosamines Used i n the Mechanism of A c t i o n Model QSAR. MOLECULE NITROSO-PIPERIDINE 2-METHYL 3-METHYL 4-METHYL 2,6-DIMETHYL 3,5-DIMETHYL 2,2,6,6-TETRAMETHYL 4-T.BUTYL 3-HYDROXY 4-HYDROXY 4-KETO 2-CARBOXY 4-CARBOXY 4-CHL0R0 3,4-DICHLORO 3,4-DIBROMO 1,2,3,6-TETRAHYDROPYRIDINE N-NITR0S0-3-PYRR0LINE N-NITROSO-HEXAMETHYLENEIMINE N-NITROSO-HEPTAMETHYLENEIMINE DIMETHYL-NITROSAMINE DIETHYL-NITROSAMINE BIS-(2-CHL0R0)BIS (2-CYANO) BIS (2-METHOXY) -

TD50 (WEEKS) 38.0 80.0 55.0 40.0 125.0 100.0 125.0 125.0 43.0 44.0 45.0 125.0 125.0 41.0 20.0 36.0 28.0 80.0 28.0 25.0 25.0 30.0 84.0 125.0 63.0

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Ε Χ Ρ

·

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25.

PETIT E T A L .

ÇSAR

Molecular

Structure

Calculator

577

Figure 4. Plot of experimental ΤΌ- (in weeks) vs. the calculated T D using the mechanism of action QSAR. TD > 100 are assigned a value of 125. >η

5 0

50

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG

578

DESIGN

Discussion 1. QSAR Independent o f Mechanism: The a p p l i c a t i o n o f c l u s t e r a n a l y s i s i s an a t t r a c t i v e method to use because r e l a t i o n s h i p s can be formulated independent of the b i o l o g i c a l data. The c a r c i n o ­ genic nitrosamines have been t r e a t e d i n such a manner. The molecular d e s c r i p t o r s F , H20, Log P, and ΔΕ were c l u s t e r analyzed. The b i o l o g i c a l data was subsequently assigned to the c l u s t e r e d p o i n t s i n the d e s c r i p t o r space. I t was then found that the potent c a r c i n o g e n i c nitrosamines c l u s t e r together, while the l e s s c a r c i n o g e n i c compounds are s c a t t e r e d over d e s c r i p t o r space (see F i g . 2 ) . These f i n d i n g s both complement and support the s i g n i f i c a n c e of eq. (9) which i s the optimuum l i n e a r r e g r e s s i o n equation found u s i n g the data of Table 1. oct dominant d e s c r i p t o r i n the a n a l y s i s , see Table 5b. I t i s n o t p o s s i b l e to g i v e a t r u l y r e l i a b l e b i o c h e m i c a l i n t e r p r e t a t i o n to t h i s f i n d i n g . How­ ever, one p o s s i b l e e x p l a n a t i o n i s that the carcinogenic- potency depends upon the bioaccumulation o f the nitrosamine i n a p a r t i c u l a r t i s s u e having a s p e c i f i c nonpolar s o l u b i l i t y . F t, the f r e e energy of i n t e r a c t i o n of a compound w i t h a 1-octanol s o l u t i o n , i s assumed to be a measure o f the nonpolar s o l u b i l i t y . oct(°Pt) = -3.9, represents the s o l v a t i o n f r e e energy o f the " t a r g e t " t i s s u e . T h i s conceptual model i n d i r e c t l y p o s t u l a t e s that t r a n s p o r t processes, as modelled through Log P, p l a y only a minor r o l e i n the mechanism o f a c t i o n . The second d e s c r i p t o r i n eqn. ( 9 ) , ΔΕ, i s found to be of minimal s i g n i f i c a n c e according to the s i n g l e v a r i a b l e ranking o f Table 5b. H20 i s ranked as the second most s i g n i f i c a n t s i n g l e v a r i a b l e i n a QSAR. However, the h i g h c o r r e l a t i o n between H20 and F , see Table 5a, e l i m i n a t e s t h i s v a r i a b l e i n m u l t i p l e v a r i a b l e l i n e a r r e g r e s s i o n equations i n v o l v i n g F t . It i s d i f f i c u l t to g i v e a physicochemical meaning to ΔΕ w i t h i n the framework of an a c t i o n mechanism. ΔΕ i s the e q u i l i b ­ rium energy d i f f e r e n c e between the most s t a b l e "boat" and " c h a i r " conformer s t a t e s . However, suppose the production of the u l t i m a t e c a r c i n o g e n i c metabolite depends upon two p a r a l l e l metabolic r e a c t i o n s as depicted i n F i g . 5a. The c o n c e n t r a t i o n , C]_, o f one metabolite i n c r e a s e s with i n c r e a s i n g ΔΕ, while the c o n c e n t r a t i o n o f the second m e t a b o l i t e , C2, decreases with i n c r e a s i n g ΔΕ, F i g . 5b. The c o n c e n t r a t i o n , C3, o f the u l t i m a t e carcinogen i s dependent upon the produce C1C2. In t h i s case the u l t i m a t e dependence o f C3 upon ΔΕ can appear to be p a r a b o l i c over some range o f ΔΕ, see F i g . 5c. T h i s e x p l a n a t i o n i s not c o n s i s t e n t with the a c t i o n mechanism assumed i n our modelling. Nor i s there any experimental support f o r or a g a i n s t a p a i r of p a r a l l e l metabolic r e a c t i o n s . However, p a r a l l e l metabolic r e a c t i o n s can be used to account f o r the r o l e of ΔΕ i n eq. ( 9 ) . F

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch025

o c t

F

i

s

t

n

e

o c

F

F

F

o c t

o c

2. QSAR Using an A c t i o n Model: Eq. (12) i n d i c a t e s that Log Ρ i s o f only marginal s i g n i f i c a n c e i n s p e c i f y i n g a c t i v i t y . The

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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PETIT E T A L .

(O

c

Figure 5. (A) Schematic of intermediate metabolite production leading to the production of the ultimate active metabolite; (B) Metabolite 1 concentration increases with increasing ΔΕ, opposite is true for Metabolite 2 concentration; (C) production (concentration) of the ultimate active metabolite exhibits parabolic dependence on ΔΕ.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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COMPUTER-ASSISTED DRUG DESIGN

optimum value f o r Log Ρ i s 1.32. This f i n d i n g i s consistent with the c l u s t e r and r e g r e s s i o n QSAR where Log Ρ was not found to be an important d e s c r i p t o r . O v e r a l l , t h i s suggests that transport processes may not be important i n the c a r c i n o g e n i c potency of these c y c l i c nitrosamines. ΔΕ appears i n eq, (12) as a minor d e s c r i p t o r whose i n c r e a s i n g value i n c r e a s e s c a r c i n o ­ g e n i c i t y (TD50 decreases). We have not been able to e x p l a i n the r o l e of ΔΕ i n t h i s QSAR. However, ΔΕ i s even l e s s important i n eq. (12) than i n eq. ( 9 ) . The r o l e of the carbonium i o n metabolites o f the nitrosamines i n s p e c i f y i n g c a r c i n o g e n i c potency can be estimated from an a n a l y s i s of V j ^ . The f o l l o w i n g conclusions have been made; 1. V41 = 1.0 i m p l i e s that secondary carbonium ions are n o t carcinogenic. Z. Vu - V21 - V31 - .5 suggests that the nature o f the s i d e chain o f the carbonium i o n i s not important t o s p e c i f y i n g c a r c i n o g e n i c potency. Further, the common d e f a u l t option to each of these cases (Χχι = X 2 i = 3 i ^ ° , i = 1,2) corresponds to the formation of -CH^©. Thus -CH3® i s estimated to be twice as c a r c i n o g e n i c as each of the three a l t e r n a t e c l a s s e s . 3. V51 - 0 i m p l i e s t h a t halogen s u b s t i t u t i o n or formation of a double bond at an adjacent carbon to the carbonium i o n enhances c a r c i n o g e n i c potency to about the same l e v e l as -CH3 w c a r c i n o g e n i c potency. 4. Q u a l i t a t i v e l y , c a r c i n o g e n i c potency can be ranked as, x

> R-C

»

R_

c - C®— C -

1

3. Summary: The two QSAR s constructed i n t h i s c u r r e n t study of c a r c i n o g e n i c c y c l i c nitrosamines a r e complementary i n that they suggest how to c o n s t r u c t a b e t t e r QSAR. F , formulated i n terms of a bioaccumulation f u n c t i o n a l , along with the carbon­ ium i o n metabolite model should be coupled together t o form a r e v i s e d QSAR a c t i o n model. Work i s underway on t h i s model p r e s e n t l y i n our l a b o r a t o r y . o c t

Acknowledgements We g r a t e f u l l y acknowledge the f i n a n c i a l support of the N a t i o n a l Cancer I n s t i t u t e ( c o n t r a c t No. NOl-CP-76927), the N a t i o n a l Science Foundation (grant No. ENV 77-74061) and the N a t i o n a l I n s t i t u t e s o f Health ( c o n t r a c t No. 217041).

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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References

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1.

The data base was provided by W. Lijinsky, Chemical Carcino-Carcinogensis Program, Frederick Cancer Research Canter, Frederick, Md. 21701 (USA). 2. W. Lijinsky and H.W. Taylor, Cancer Lett., 1,359 (1976). 3. W. Lijinsky and H.W. Taylor, Cancer Res., 35, 1270 (1975). 4. W. Lijinsky and H.W. Taylor, Cancer Res., 36, 1988 (1976). 5. G.M. Singer, H.W. Taylor, and W. Lijinsky, Chem.-Biol. Interactions, 19, 133 (1977). 6. J.S. Wishnok, M.C. Archer, A.S. Edelman, and W.M. Rand, Chem. -Biol. Interactions, 20, 43 (1978). 7. See, E.J. Ariens, Drug Design, Academic Press, New York Vols. 1-6 (1971-1976). 8. A.J. Hopfinger, Conformational Properties of Macromolecules, Academic Press, New (1973). 9. L.B. Kier, Molecular Orbital Theory in Drug Research, Academic Press, New York (1971). 10. R. Rekker, The Hydrophobic Fragment Constant, (Elsevier, New York), (1977). 11. A. Leo, Table of Common Fragment Constants, Dept. Chemistry, Pomona College, Claremont, CA (1976). 12. J. Hine and P.D. Mookerjee, J . Org. Chem., 40, 292 (1975). 13. C. Hansch, A. Leo, S.H. Unger, K.H. Kim, D. Nikaitami, and E.J. Lien, J. Med. Chem., 16, 1207 (1973). 14. A.J. Hopfinger and R.D. Battershell, J. Med. Chem., 19, 569 (1976). 15. N.L. Allinger, J.T. Sprague and T. Kiljefors, J . Am. Chem. 96, 5100 (1974). 16. R. Potenzone, Jr., E. Cavicchi, H.J.R. Weintraub, and A.J. Hopfinger, Computers and Chem., 1, 187 (1977). 17. I.D. Blackburne, R.P. Duke, R.A.Y. Jones, A.R. Katritsky, and K.A.F. Record, J. Chem. Soc. Perkins II, 2, 332 (1972). 18. O. Gropen and P.N. Skancke, Acta, Chem. Scand., 25, 1241 (1971). 19. a. R.K. Harris and R.A. Spragg, J. Mol. Spect. 23, 158 (1967). b. Y.L. Chow and C.J. Colon, Canad. J. Chem., 46, 2827 (1968). c. R.K. Harris and R.A. Spragg, J. Mol. Spect., 30, 77 (1969). 20. W. Lijinsky and H.W. Taylor, Int. J. Cancer, 16, 318 (1975). 21. J.A. Pople and D.C. Beveridge, "Approximate Molecular Orbital Theory" (McGraw-Hill, New York) (1970). 22. a. R.C. Bingham, M.J.S. Dewar, and D.H. Lo, J. Am. Chem. Soc., 97, 1285 (1975). b. R.C. Bingham, M.J.S. Dewar, and D.H. Lo, J. Am. Chem. Soc., 97, 1302 (1975). 23. See, M.S. Tute, in Advances in Drug Research (N.J. Harper and A.B. Simmons, eds.) Academic Press, New York, Vol. 6, p. 1, (1971). 24. T.T. Young and T.W. Calvert, Classification, Estimation, and Pattern Recognition, Elsevier, New York (1974). RECEIVED

June 8, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

26 Computer-Aided Selection of Novel Antitumor Drugs for Animal Screening LOUIS HODES

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

National Cancer Institute, 8300 Colesville Road, Silver Spring, MD 20910

An earlier paper (1) described a method for estimating the probability of activity of compounds. In that report the method was applied to a small set of data for the purpose of comparing the performance to that of more sophisticated pattern recognition methods. The intended application was the large volume of data from the antitumor screening program of the National Cancer Institute (NCI). Early in 1976 a new panel of animal models for screening was adopted. These include mouse colon, breast, and lung tumors; and corresponding human tumor xenografts in athymic mice. Most compounds are required to show activity in an in vivo pre-screen in order to receive the more extensive testing. P388 mouse lymphocytic leukemia was chosen as the pre-screen and, thus, P388 became the logical choice for a trial of the statistical-heuristic method. There were already substantial amounts of P388 data from earlier tests, and roughly 15,000 compounds a year are currently being screened in P388. From t h i s data two trials o f the method were designed to approximate its use in the operating environment. These a r e d e s c r i b e d l a t e r as experiments 1 and 2. A s e r i e s of enhancements followed. Some a r e reported on here, while others a r e s t i l l being worked on. There a r e two aspects of t h i s method i n the s e l e c t i o n o f compounds f o r antitumor screening. The f i r s t can be considered an enrichment i n the y i e l d of a c t i v e s . For example, suppose we can achieve an enrichment f a c t o r of 1.2 by t a k i n g a r b i t r a r i l y j u s t those compounds s c o r i n g i n the top 50%. In that case, i n s t e a d of screening 15,000 compounds, NCI can o b t a i n the same number o f P388 a c t i v e s by screening 12,500 compounds which were d e r i v e d from an i n i t i a l e v a l u a t i o n of 25,000 compounds by t h i s computer method. Such a model i s envisioned as p a r t of a p r e s e l e c t i o n module attached a t the beginning of the Drug Research and Development automated chemical i n f o r m a t i o n system. This module w i l l evaluate chemical s t r u c t u r e s p r i o r t o a c q u i s i t i o n . I t w i l l i n c l u d e the c u r r e n t l y performed search f o r d u p l i c a t e s , as w e l l as a comparison This chapter not subject to U . S . copyright. Published 1979 A m e r i c a n C h e m i c a l Society

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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with an extensive l i s t of skeleton s t r u c t u r e s to detect analogs. A comprehensive r e p o r t would then be examined by the chemist r e s p o n s i b l e f o r a c q u i s i t i o n , who w i l l decide whether to acquire the compound and, i f so, whether s p e c i a l c o n s i d e r a t i o n or t e s t i n g is called for. The second aspect of the method i s s e l e c t i o n by s u r v e i l a n c e . This would i n v o l v e running even l a r g e r numbers of compounds through the model, perhaps a l l new Chemical A b s t r a c t s r e g i s t r a t i o n s . Under these c o n d i t i o n s , only the high s c o r i n g compounds would be reviewed manually. In c o n t r a s t , under the f i r s t aspect, even the lowest s c o r i n g can be reviewed. The main requirement under both aspects i s the a b i l i t y to detect new a c t i v e c l a s s e s of compounds. Therefore, the f i r s t enhancement of the method was the e l i m i n a t i o n of f a m i l i a r drugs from the t r a i n i n g s e t , f o l l o w i n g the o r i g i n a l v e r s i o n of the method (2). I t w i l l be seen that the r e s u l t i n g model gives higher scores to compounds with r e l a t i v e l y u n f a m i l i a r s t r u c t u r e s which have appeared i n a c t i v e P388 t e s t s . These compounds are more i n demand f o r f u r t h e r development than are analogs of known drugs. A l s o , c e r t a i n other p r o p e r t i e s of the method point i t toward novel s t r u c t u r e s . Since each f e a t u r e i s t r e a t e d independently, new combinations of f e a t u r e s which have not appeared together before are more l i k e l y to be s e l e c t e d i n t h i s method than i n other more elaborate methods. Moreover, as w i l l be seen l a t e r , a m o d i f i c a t i o n of the method gives more weight to lower incidence f e a t u r e s . No f e a t u r e i s discarded because of low incidence alone. In a d d i t i o n , a separate program p r i n t s out, f o r each candidate compound, i t s lowest i n c i d e n c e f e a t u r e i n P388 t e s t i n g as w e l l as a l l f e a t u r e s not yet having occurred i n P388 t e s t i n g . It must be emphasized that although t h i s method runs on a computer, i t i s not designed to a u t o m a t i c a l l y pass or r e j e c t compounds. Rather, i t i s proposed as a t o o l to a i d the m e d i c i n a l chemist i n s e l e c t i n g compounds. Although i t s assumption of f e a t u r e independence i s a strong l i m i t a t i o n , the unbiased use of much data should make the scores u s e f u l . Review of the Method. The method was descibed p r e v i o u s l y (1) so only a b r i e f review w i l l be attempted here. Some m o d i f i c a t i o n s are discussed i n l a t e r s e c t i o n s of t h i s paper. A model i s based on a c o l l e c t i o n of compounds of known a c t i v i t y , c a l l e d the t r a i n i n g s e t . A set of f e a t u r e s p e r t a i n i n g to these compounds are produced; we use molecular substructure descriptors. These f e a t u r e s must, of course, be g e n e r a l l y r e l e v a n t to a c t i v i t y f o r the method to work. An a c t i v i t y weight i s assigned to each f e a t u r e independently. This weight i s based on c i r c u m s t a n t i a l evidence, that i s , on how o f t e n the f e a t u r e occurs i n the a c t i v e compounds of the t r a i n i n g set r e l a t i v e to how o f t e n i t i s expected to occur assuming that

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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the f e a t u r e i s not r e l e v a n t to a c t i v i t y . In computing the expected i n c i d e n c e , we use as reference the i n c i d e n c e of the f e a t u r e i n the e n t i r e Drug Research and Development c o l l e c t i o n . The weight i s expressed as a number of standard d e v i a t i o n s using the s t a t i s t i c a l d i s t r i b u t i o n derived from c o n s i d e r i n g the a c t i v e compounds as a random s e l e c t i o n from the f i l e . This procedure compensates f o r the wide range of incidences among s t r u c t u r e features. The f e a t u r e s c u r r e n t l y are those r o u t i n e l y generated as keys f o r the substructure i n q u i r y system.(3) This system incorporates an open-ended f e a t u r e set as opposed to a d i c t i o n a r y . The main types of keys are the augmented atom (AA), the g a n g l i a augmented atom (GAA) the r i n g key and two kinds of nucleus key, i n a d d i t i o n to i n d i v i d u a l element keys. The number of f e a t u r e s appearing i n the P388 data are roughly 2000 without the GAA keys i n c r e a s i n g to roughly 8000 when the GAA keys are s u b s t i t u t e d f o r the AA keys. Other f e a t u r e s being considered are keys used i n the BASIC search system (4) and an a l g o r i t h m i c approximation to f u n c t i o n a l groups. The d i f f e r e n t c l a s s e s of f e a t u r e s w i l l be covered l a t e r . An a c t i v i t y score i s produced f o r a compound of presumably unknown a c t i v i t y by adding the weights of the f e a t u r e s i t presents. The score i s not intended to estimate the s t r e n g t h of a c t i v i t y , but only some measure of the l i k e l i h o o d that the compound i s a c t i v e . Experiments with a Large Data Set. Several experiments were performed to e s t a b l i s h the f e a s i b i l i t y of t h i s method on l a r g e amounts of data. These experiments r e q u i r e d a few searches of the Drug Research and Development b i o l o g i c a l f i l e to f i n d compounds that met v a r i o u s c r i t e r i a as a r e s u l t of P388 t e s t i n g . These c r i t e r i a are u s u a l l y s t a t e d i n terms of the T/C r a t i o , which i s the median l i f e - s p a n of the t r e a t e d animals d i v i d e d by that of the c o n t r o l s . The output of each b i o l o g i c a l search i s a l i s t of NSC numbers. * hese numbers are assigned s u c c e s s i v e l y to each compound upon r e g i s t r a t i o n of that compound i n the chemical information system (CIS). This occurs upon acceptance of the compound f o r screening. NSC number 1 was assigned i n 1955 and current (1979) NSC numbers are over 300,000. The r e s u l t s of the b i o l o g i c a l search are then sent to the CIS f o r e x t r a c t i o n of the s t r u c t u r e keys to be used as f e a t u r e s . This s e c t i o n d e s c r i b e s the experiments that were performed before the w e l l known c l a s s e s were removed. They showed that the l a r g e number of compounds and f e a t u r e s could e a s i l y be handled. It w i l l be seen l a t e r that removing the c l a s s e s of compounds l e d to some b a s i c changes i n the model. A l s o , i t w i l l be i n t e r e s t i n g to compare the r e s u l t s of the modified model. P r e l i m i n a r y Experiments. In November, 1975 a search of the b i o l o g i c a l f i l e s produced a l i s t of a c t i v e and a l i s t of i n a c t i v e

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compounds w i t h r e s p e c t to P388 according to the f o l l o w i n g criteria. The a c t i v e s were picked from a f i l e of roughly 6000 s e l e c t e d agents and amounted to 489 compounds with a manually assigned code i n d i c a t i n g s i g n i f i c a n t a c t i v i t y i n P388 ( t h i s was based on a confirmed T/C of 175% or g r e a t e r . ) The i n a c t i v e compounds, numbering 4174, were c o l l e c t e d from two sources. (1) Compounds from the s e l e c t e d agents f i l e which had been assigned a manual code s i g n i f y i n g n e g a t i v e i n P388. (2) Compounds w i t h i n the l a t e s t 100,000 NSC number range which had d e f i n i t i v e P388 t e s t i n g w i t h T/C always l e s s than 175%. D e f i n i t i v e t e s t i n g r e q u i r e s a regimen of at l e a s t three dose l e v e l s w i t h the bottom two non-toxic. T o x i c i t y i s d e f i n e d as a T/C l e s s than 85% or l e s s than 2/3 s u r v i v o r s on i n i t i a l t o x i c i t y day. An a d d i t i o n a l weight l o s s c r i t e r i o n was not used. The p r e l i m i n a r y experiments used these compounds mostly as t r a i n i n g s e t s . At f i r s t , every t e n t h compound i n the NSC sequence beginning with the f i r s t was s e l e c t e d to be included i n a t e s t set, l e a v i n g the remaining 90% as the t r a i n i n g s e t . A second cut c o n s i s t e d of every t e n t h compound s t a r t i n g with the second. The a c t i v e s and i n a c t i v e s were cut s e p a r a t e l y to e q u a l i z e t h e i r r e l a t i v e i n c i d e n c e i n the t e s t and t r a i n i n g s e t s . F i v e such cuts were run. In summary, these f i v e cuts contained 236 a c t i v e compounds. (Of the 489 a c t i v e compounds, s e v e r a l were d i s q u a l i f i e d because they lacked chemical s t r u c t u r e keys, so that 236 a r e about h a l f of those remaining.) Only 5 of the 236 compounds ranked i n the lower 50% of the a c t i v i t y scores i n t h e i r r e s p e c t i v e c u t s . This remarkable performance i s due i n l a r g e measure to h e a v i l y populated c l a s s e s of s i m i l a r compounds o c c u r r i n g i n the f i l e of s e l e c t e d agents. Nevertheless, these r e s u l t s were considered s u f f i c i e n t l y encouraging to t r y data c l o s e r to c u r r e n t input. T h i s t r i a l a l s o r e v e a l e d p r o p e r t i e s of the method as a p p l i e d to the P388 prescreen that warrant f u r t h e r a t t e n t i o n . F i r s t , the i n a c t i v i t y score was not u s e f u l , so that the r e s u l t s were e q u a l l y good when i t was ignored. Second, conspicuous i n the small number of low s c o r i n g P388 a c t i v e compounds were 5 - f l u o r o u r a c i l , platinums and e l l i p t i c i n e s , s i n c e they are of great i n t e r e s t i n the treatment of human cancer. A l s o , these f a i l u r e s represented the three main c a t e g o r i e s of failure. The platinum scores increased upon b e t t e r data as described soon. More powerful f e a t u r e s a r e r e q u i r e d f o r compounds l i k e 5 - f l u o r o u r a c i l , whereas e l l i p t i c i n e s a r e more i n t r a c t a b l e s i n c e there a r e many i n a c t i v e s w i t h the same b a s i c s t r u c t u r e . A l l examples of these three compounds were l a t e r removed as analogs of w e l l known c l a s s e s . Test Set 1. A more r e a l i s t i c t r i a l was the s e l e c t i o n , as a t e s t s e t , of compounds as they had been input i n t o the program. The 5,000 compounds from NSC number 260,001 through 265,000 were s e l e c t e d as having a f a i r amount of P388 t e s t i n g a t the time. (October, 1976.) These were c a t e g o r i z e d by manual review of the

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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screening data summaries as f o l l o w s according to t h e i r a c t i v i t y i n P388. Ά ' — T / C at l e a s t 175% i n two separate screening t e s t s . » C — T / C at l e a s t 120% i n two separate screening t e s t s but not i n category A. Two t e s t s i n P388 w i t h T/C of 120% or greater i s s u f f i c i e n t to be considered a candidate f o r t e s t i n g i n the tumor p a n e l . 'D'—T/C a t l e a s t 120% i n one screening t e s t and not y e t r e t e s t e d . Έ ' — T / C a t l e a s t 120% i n one screening t e s t and T/C l e s s than 120% i n a separate screening t e s t and not i n category C or A. N — T / C l e s s than 120% i n a l l screening t e s t s . Must have a t e s t with a t l e a s t three dose l e v e l s , the bottom two non-toxic. M — i n s u f f i c i e n t t e s t i n g i n P388. T — not t e s t e d a t a l l i n P388. The t r a i n i n g s e t . There were reasons that performance on the C s could be improved by beginning again with a new t r a i n i n g s e t . F i r s t , there were a few f a l s e negative platinum compounds, and i t was n o t i c e d that the platinum key was not weighted h i g h l y simply because of a time l a g i n a s s i g n i n g compounds to the s e l e c t e d agents f i l e w i t h the a p p r o p r i a t e manual code. Second, i t was f e l t that a t r a i n i n g s e t c o n t a i n i n g C's as w e l l as A s should perform b e t t e r on incoming s e l e c t i o n s which would y i e l d T/C between 120% and 175%. T h i r d , a search of the e n t i r e f i l e r a t h e r than the most recent 100,000 compounds, and a T/C c u t o f f of 120% might make the i n a c t i v e t r a i n i n g set more u s e f u l . Thus, a more comprehensive t r a i n i n g set was c o l l e c t e d from the b i o l o g i c a l f i l e . The search took p l a c e e a r l y i n 1977 and covered NSC numbers 1 through 260,000. NSC number 260,000 corresponds c h r o n o l o g i c a l l y to near the end of 1975, so b i o l o g i c a l t e s t i n g should have been f a i r l y complete. F i v e l i s t s of NSC numbers were c o l l e c t e d according to degree of a c t i v i t y i n P388. The search of the b i o l o g i c a l f i l e was s p e c i f i e d according to the c a t e g o r i e s A, C, D, Ε and Ν e s t a b l i s h e d earlier. From the truncated f i l e of 260,000 compounds, category A yielded 880 compounds, category C y i e l d e d 1916 compounds, category D y i e l d e d 1402 compounds, category Ε y i e l d e d 1787 compounds, category Ν y i e l d e d 15524 compounds, f o r a t r a i n i n g s e t t o t a l of 21509 compounds i n P388. Experiment 1. The t e s t s e t f o r t h i s experiment c o n s i s t e d of the 5000 compounds from NSC number 260001 to 265000, of which 2322 s a t i s f i e d the b i o l o g i c a l t e s t i n g and chemical s t r u c t u r e data requirements. Various combinations of weights and scores d e r i v e d from the s e t s of A s , C s and N s of the t r a i n i n g set were t r i e d w i t h the f o l l o w i n g r e s u l t s . F i r s t , the 880 A s alone were used as the t r a i n i n g s e t and the 2322 compounds were scored and ranked, As shown i n Table I, a l l 26 A s scored i n the upper h a l f but there were 11 C s out o f 85 i n the lower h a l f . f

f

f

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

f

f

f

f

f

1

f

f

f

1

1

f

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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588

Table I . Ranking of A c t i v e s i n Test Set 1. T r a i n i n g s e t A.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

RANK (Deciles)

NUMBER OF A COMPOUNDS

10 9 8 7 6

18 5 1 2 0

5 4 3 2 1

0 0 0 0 0

CUM. PERCENT 69 88 92 100

NUMBER OF C COMPOUNDS

CUM. PERCENT

41 19 5 3 6

48 71 76 80 87

5 1 4 1 0

93 94 99 100

1

f

A new t r a i n i n g s e t was formed by combining the A s and C s so that there were now 880 + 1916 = 2796 compounds i n the t r a i n i n g set. A c t u a l l y , each of the A compounds was counted as appearing twice i n the t r a i n i n g s e t , so the weightings r e s u l t e d i n what may be considered a 2A+C model. Now, 1 A out of 26 i n the t e s t s e t and 7 C s of 85 f e l l i n t o the lower h a l f . See Table I I . Again, the weights d e r i v e d from the r a t h e r l a r g e s e t of i n a c t i v e s d i d not help the performance. 1

Table I I . Ranking of A c t i v e s i n Test Set 1. T r a i n i n g s e t 2A+C. RANK (Deciles)

NUMBER OF A COMPOUNDS

10 9 8 7 6

15 8 0 2 0

5 4 3 2 1

0 1 0 0 0

CUM. PERCENT 58 88 92

100

NUMBER OF C COMPOUNDS

CUM. PERCENT

41 20 8 5 4

48 72 81 87 92

2 1 2 2 0

94 95 98 100

Expressed as an enrichment of the y i e l d o f a c t i v e s , these r e s u l t s show that s e l e c t i n g the upper h a l f under the 2A+C model would have changed the y i e l d of a c t i v e s from 111 out of 2322 or 4.8% to 103 out of 1161 or 8.9% Experiment 2. An attempt was now made to s e l e c t a sequence

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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Drugs

of compounds which seemed r e l a t i v e l y f r e e of analogs. The new t e s t set chosen c o n s i s t e d of compounds w i t h NSC numbers 268001 through 272000. This t e s t s e t , l i k e the e a r l i e r one, was r a t e d i n t o b i o l o g i c a l c a t e g o r i e s A,C,D,E,N,M,T by manual review of the screening data summaries. Excluding M s and T s and compounds w i t h no chemical s t r u c t u r e keys, there were 3239 compounds l e f t t o t a l l y , of which 32 were A s and 145 were C s . Upon running the same 2A+C model, a l l 32 A s scored i n the upper h a l f and 45 out of 145 C s scored i n the lower h a l f . The r e s u l t s are summarized i n Table I I I . Expressed as an enrichment, the y i e l d went from 177 out of 3239, or 5.5%, to 132 out of 1620 f o r the upper h a l f or 8.1%. This time a l l the A s scored i n the upper 50% w i t h respect to the 2A+C model. f

f

1

f

1

f

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

f

Table I I I . Ranking of A c t i v e s i n Test Set 2. T r a i n i n g set 2A+C. RANK (Deciles)

NUMBER OF A COMPOUNDS

10 9 8 7 6

27 5 0 0 0

5 4 3 2 1

0 0 0 0 0

CUM. PERCENT 84 100

NUMBER OF C COMPOUNDS

CUM. PERCENT

41 24 15 13 7

28 45 55 64 69

10 10 11 7 9

76 83 90 95 100

Removal of Analogs. At t h i s point the model could be considered extremely s u c c e s s f u l from the point of view of enrichment of the y i e l d of actives. But, i t s performance depends to a l a r g e extent on the continued t e s t i n g of analogs of w e l l known a c t i v e compounds. The main purpose of P388 t e s t i n g and a l s o of the model remains the discovery of new a c t i v e c l a s s e s . The p r o f i c i e n c y of the model toward t h i s end must be enhanced and i t s e f f e c t i v e n e s s measured. Analogs of the w e l l known a c t i v e compounds, which w i l l now be r e f e r r e d to simply as analogs, make up a l a r g e part of the t r a i n i n g s e t . More than 85% of the h i g h l y a c t i v e A s and over one t h i r d of the C s belong to these c l a s s e s , .. h e r e f o r e , any new t r a i n i n g set formed without them should produce s u b s t a n t i a l l y different results. I t i s c l e a r that the new model w i l l not perform as w e l l on f

f

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED

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590

DRUG DESIGN

any f u r t h e r analogs of those removed. Many of the p r e v i o u s l y most h i g h l y weighted f e a t u r e s w i l l now be decreased i n weight or e l s e be completely absent from the model. Hence, the new model w i l l tend to show decreased p r e d i c t a b i l i t y on a t e s t set to the extent that i t contains analogs. R e c a l l that a p r o v i s i o n f o r d e t e c t i n g analogs i s i n c l u d e d i n the s e l e c t i o n process. On the other hand, the presence of l a r g e numbers of analogs i n the t r a i n i n g set can d e t e r i o r a t e performance of the model on those compounds which may p r o v i d e new l e a d s . T h i s occurs when a known a c t i v e group such as an a l k y l a t i n g f u n c t i o n i s combined w i t h otherwise i n a c t i v e m o i e t i e s , producing an a c t i v e compound. The weights of a l l i t s keys i s r a i s e d . When such keys occur i n i n a c t i v e compounds they can r a i s e t h e i r score s u f f i c i e n t l y to y i e l d many f a l s e p o s i t i v e s . F a l s e p o s i t i v e s , of course, w i l l lower the r e l a t i v e rank of the t r u e p o s i t i v e s which score below them. Removal of analogs from the t r a i n i n g set was f i r s t performed on the h i g h l y a c t i v e A s by Ken P a u l l , then with Starks C. P., the a c q u i s i t i o n s c o n t r a c t o r . He presented Table IV, which c l a s s i f i e s analogs among the 846 A s w i t h d e f i n e d s t r u c t u r e . Familiar a l k y l a t i n g agents, which i n c l u d e mustards, methanesulfonates, epoxides, a z i r i d i n e s and n i t r o s o u r e a s , make up 52% of the 846. Other, more s p e c i a l i z e d c l a s s e s reduced the A s f u r t h e r u n t i l they were cut by 87%. 1

1

1

f

f

Table IV. A c t i v e C l a s s e s i n A T r a i n i n g Set. 846 S t r u c t u r e s w i t h P388 T/C % >175% CLASS

NUMBER

A l k y l a t i n g Agents Anthracyclines Wander Antifols Actinomycins Nucleocides 9-Aminoacr i d i n e Platinum Planar Quaternary P o l y c y c l i c s T r i t y l cysteines Quinoliniums Mosemicarbizones Hydrazonoyl h a l i d e s Thioxanthenones Diazo compounds

440 50 50 32 23 22 20 19 18 16 14 9 9 8 7

CUM.

PERCENT 52% 64%

70%

82%

87%

f

The r e d u c t i o n on the C s was l e s s d r a s t i c , the number of compounds going from 1916 to 1182. Several a d d i t i o n a l classes were removed as shown i n Table V. The s e l e c t i o n was performed

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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by Ken P a u l l i n c o o r d i n a t i o n with Mike Hazard and Bob Ing of NCI.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

Table V. A d d i t i o n a l A c t i v e Classes from T r a i n i n g Sets. Bruceantin Halacanthane Colchicine Antimony Hydroxyurea Phosphonium Triazeno Emetine Methyl GAG

Removed

Podophyllotoxin Phenazine Cycloleucine Mithramycin Charged Nitrogen Sulfonium Ellipticine Vincristine S t y r y l Quinoline

Of course, many compounds i n most of these a c t i v e c l a s s e s t e s t e d negative i n P388. A great many others were not t e s t e d a t a l l i n P388. I d e a l l y , one would d e s i r e a new f i l e with a l l these compounds e l i m i n a t e d . R e c a l l that the method uses the i n c i d e n c e of a f e a t u r e i n the e n t i r e f i l e as a r e f e r e n c e . The analogs i n the f i l e would d i s t o r t the s t a t i s t i c s f o r the same reasons given earlier. However, i t was i m p r a c t i c a l to search a l l those c l a s s e s over the e n t i r e f i l e . Machine searches would consume too much computer time. It was p r a c t i c a l to remove the analogs from the s e t of P388 i n a c t i v e s . Machine searches f o r a l l the c l a s s e s were performed by Mike Hazard and Frank S o r d y l , reducing the i n a c t i v e s from 15524 to 14357 compounds. The method must now be r e v i s e d so that the t r a i n i n g s e t r a t h e r than the e n t i r e f i l e provides the r e f e r e n c e f o r the expected i n c i d e n c e of a f e a t u r e among the a c t i v e s . Thus, a f e a t u r e would have p o s i t i v e weight i f i t s p r o p o r t i o n a l i n c i d e n c e were greater i n the a c t i v e s than i n the i n a c t i v e s . C o r r e c t i o n of the Method. A c o r r e c t i o n to a more p r e c i s e model became more imperative when the removal of analogs induced the universe of compounds to be l i m i t e d to the t r a i n i n g s e t , as depicted i n the preceding section. The method as d e s c r i b e d i n (1) assumes, under the n u l l hypothesis, that the a c t i v e compounds are a random s e l e c t i o n of compounds from the f i l e . The p r o b a b i l i t y of f e a t u r e i n c i d e n c e i n the a c t i v e s was s a i d to f o l l o w the binomial d i s t r i b u t i o n . Robert Tarone of NCI advised me as f o l l o w s . 1) The binomial d i s t r i b u t i o n holds only when the random s e l e c t i o n i s done with replacement. 2) A more p r e c i s e model should assume random s e l e c t i o n without replacement. 3) Feature i n c i d e n c e i n the

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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592 a c t i v e s then f o l l o w s the hypergeometric standard d e v i a t i o n , S, i s now given by 2

distribution.

DRUG DESIGN

4) The

2

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

S = (F(T-F)N(T-N))/(T (T-l)). Here F i s the number of compounds w i t h the f e a t u r e and Τ i s the t o t a l number of compounds, now the number of compounds i n the t r a i n i n g s e t . Ν i s the number of a c t i v e s , so now T-N i s the number of i n a c t i v e s . Under these c o n d i t i o n s there i s e f f e c t i v e l y one weight f o r each f e a t u r e , s i n c e the a c t i v e and i n a c t i v e weights become equal i n magnitude and opposite i n s i g n . The same holds t r u e f o r the scores f o r each p r e d i c t e d compound. Thus, when the t r a i n i n g s e t i s the u n i v e r s e of compounds, there i s only one a c t i v i t y score. The i n a c t i v i t y score which had not proved u s e f u l anyway, being reduntant, can be ignored. If Ν i s much l e s s than Τ then the hypergeometric d i s t r i b u t i o n becomes i n d i s t i n g u i s h a b l e from the binomial d i s t r i b u t i o n where S*=P(1-P)N and Ρ i s simply F/T. This c o n d i t i o n c e r t a i n l y holds when the e n t i r e f i l e i s used as a r e f e r e n c e . I t i s even a good approximation when only the t r a i n i n g set i s used s i n c e the a c t i v e s are much l e s s numerous than the i n a c t i v e s . However, the c o r r e c t i o n was necessary upon c o n s i d e r a t i o n of weights f o r m u l t i p l e occurrences of f e a t u r e s . Here, f o r example, when computing the weight f o r two or more occurrences of a f e a t u r e the above formula f o r the standard d e v i a t i o n becomes 2

2

S = ( F (F-F )Hj (F-N ) ) / ( F ( F - l ) ) · 2

2

1

Here F i s , as before, the number of compounds w i t h one or more occurrences of the f e a t u r e , F^ i s the number of compounds with two or more occurrences and N| i s the number of a c t i v e s with the f e a t u r e . Now, i f the f e a t u r e happens to be more prominent i n the a c t i v e s than i n the i n a c t i v e s , then N^ can be s i g n i f i c a n t compared w i t h F. Thus, i n some cases the c o r r e c t e d v e r s i o n w i l l show a s i g n i f i c a n t l y d i f f e r e n t weight. These d i f f e r e n c e s a r e much more l i k e l y when the t r a i n i n g s e t becomes the r e f e r e n c e u n i v e r s e . M o d i f i c a t i o n of the Method. The removal of analogs accentuated a weakness of the method which allowed some h i g h l y p r e v a l e n t f e a t u r e s to r e c e i v e weights of much l a r g e r magnitude than seems reasonable. For example, keys l i k e benzene and s i x - c a r b o n sugars showed i n c i d e n c e s i n the a c t i v e s that were between f i v e and ten standard d e v i a t i o n s away from t h e i r expected i n c i d e n c e s . Before the removal of analogs, these numbers were dominated by the higher weighted analog keys such as a z i r i d i n e which ranged i n t o the twenties and h i g h e r . In the new model the presumably innocuous keys exerted a dominant

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

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i n f l u e n c e and became more o b v i o u s l y troublesome. I t was necessary to modify the method so that such f e a t u r e s are a u t o m a t i c a l l y deemphasized. The anomalous e f f e c t i s due to the f a c t that a r e l a t i v e l y minor d e v i a t i o n from the expected incidence i n the a c t i v e s of a h i g h incidence f e a t u r e has a l a r g e s t a t i s t i c a l s i g n i f i c a n c e . For example, a f e a t u r e with 60% i n c i d e n c e , which i s expected to occur i n 1000 out of 1667 a c t i v e s has standard d e v i a t i o n approximately 20. Thus, the chance that i t occurs i n more than 1100 or l e s s than 900 a c t i v e s i s f i v e standard d e v i a t i o n s away. The model i s based on random s e l e c t i o n , but of course the s e l e c t i o n of compounds i s not r e a l l y random. The l a r g e d e v i a t i o n s are due to s e l e c t i o n parameters which may or may not be r e l e v a n t to a c t i v i t y , but which tend to give high incidence f e a t u r e s increased e f f e c t . A h e u r i s t i c f o r reducing the magnitude of these weights i s simply the d i v i s i o n of the computed weight of each f e a t u r e by the logarithm of i t s i n c i d e n c e . We use the incidence i n the t r a i n i n g set of about 15000 compounds, a f t e r the removal of analogs. To i l l u s t r a t e , we can d i v i d e the weight by the logarithm to the base ten of the i n c i d e n c e f o r every f e a t u r e with i n c i d e n c e greater than ten, so that no weight i s i n c r e a s e d . R e c a l l that l o g 10 = 1. So, f o r example, a f e a t u r e that occurs 100 times w i l l have i t s weight d i v i d e d by two; i f i t occurs 1000 times i t s weight i s d i v i d e d by 3; e t c . This m o d i f i c a t i o n of the weights has the s e r e n d i p i t o u s e f f e c t of emphasizing low incidence f e a t u r e s , which helps point the model toward the d i s c o v e r y of new c l a s s e s . R e s u l t s without

Analogs .

A new model c o n s i s t e d of weights generated from the t r a i n i n g set without analogs. T h i s model r e q u i r e d the c o r r e c t i o n described e a r l i e r . R e s u l t s are to be compared with those from the o l d model i n c l u d i n g analogs. A f u r t h e r model incorporated the m o d i f i c a t i o n based on i n c i d e n c e . Since the r a t i o of C's to A s a f t e r the removal of analogs increased to more than ten to one, a 5A+C model, presenting each A f i v e times, replaced the 2A+C model used e a r l i e r . The f i v e to one r a t i o was a h e u r i s t i c compromise; something l i k e ten to one g i v i n g too much i n f l u e n c e to i n d i v i d u a l compounds. R e s u l t s on the Test Set. Results on t e s t set 2, which contained fewer analogs, are more comparable to the e a r l i e r results. The new r e s u l t s are shown i n Table VI. Compared with Table I I I , performance on the A s d e t e r i o r a t e s somewhat, but r e s u l t s on the C s are about the same. O v e r a l l , the top 50% contained 70% of the a c t i v e s , compared w i t h 75% e a r l i e r . 1

T

f

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

Table V I . Ranking of A c t i v e s i n Test Set 2. T r a i n i n g s e t 5A+C. NUMBER OF A COMPOUNDS

10 9 8 7 6

19 3 2 1 1

59 68 75 78 81

40 15 11 21 12

28 40 46 60 68

5 4 3 2 1

0 1 3 2 0

84 94 100

13 10 9 11 3

77 84 90 98 100

CUM. PERCENT

NUMBER OF C COMPOUNDS

CUM. PERCENT

RANK (Deciles)

The r e s u l t s a f t e r the i n c i d e n c e m o d i f i c a t i o n a r e shown i n Table V I I . Performance on the A compounds i s e f f e c t i v e l y the same. Performance on the C's i s improved by the incidence m o d i f i c a t i o n , but not s i g n i f i c a n t l y . Table V I I . Ranking of A c t i v e s i n Test Set 2. T r a i n i n g set 5A+C. A f t e r Incidence M o d i f i c a t i o n . RANK (Deciles)

NUMBER OF A COMPOUNDS

10 9 8 7 6

18 4 2 2 0

5 4 3 2 1

0 1 3 2 0

CUM. PERCENT 56 69 75 81

84 94 100

NUMBER OF C COMPOUNDS

CUM. PERCENT

42 17 17 16 12

29 41 52 63 72

9 15 4 10 3

78 88 91 98 100

As expected, the removal of analogs lowers the o v e r a l l performance of the model. However, i t i s a l s o p o s s i b l e to get a b e t t e r i n d i c a t i o n of i t s performance on novel compounds as follows. The a c t i v e s (A+C) i n the t e s t sets were examined to f l a g analogs according to the c r i t e r i a used i n removing them from the t r a i n i n g s e t . There were only twenty a c t i v e non-analogs i n the 2322 compounds of t e s t s e t 1 and 72 i n the 3239 compounds of t e s t

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

26.

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set 2. F u r t h e r , these compounds tend to come i n small c l u s t e r s of s i m i l a r s t r u c t u r e s so the d i v e r s i t y i s q u i t e l i m i t e d , e s p e c i a l l y on t e s t set 1. The r e s u l t s on the 68 non-analogs that r a t e d C i n t e s t set 2 are shown i n Table V I I I f o r three v e r s i o n s of the model. The two v e r s i o n s of the 5A+C-analogs model, before and a f t e r the i n c i d e n c e m o d i f i c a t i o n , d i d not show much d i f f e r e n c e , but the d i f f e r e n c e from the 2A+C model may be s i g n i f i c a n t . Table V I I I . Ranking of Non-Analogs i n Test

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

RANK (Deciles)

2A+C MODEL NO. CUM.%

5A+C MODEL CUM.% NO.

Set 2.

WITH INCID. MOI CUM.% NO.

10 9 8 7 6

11 10 8 7 5

16 31 43 53 60

18 9 6 6 5

26 40 49 57 65

20 8 6 6 4

29 41 50 59 65

5 4 3 2 1

4 8 6 3 6

66 78 87 91 100

7 5 3 7 2

75 82 87 97 100

6 7 2 7 2

74 84 87 97 100

f

The non-analogs do not do q u i t e as w e l l as the t o t a l C s i n t h e i r r e s p e c t i v e models. At l e a s t i n t h i s t e s t s e t , the analogs tend to score f a i r l y high, even when they have been removed from the t r a i n i n g s e t . The T r a i n i n g Set as a Test Set. I t has j u s t been shown that the r e s u l t s on the t e s t set do not provide a completely s a t i s f a c t o r y i n d i c a t i o n of any e f f e c t of removing analogs from the t r a i n i n g s e t . However, the t r a i n i n g set minus anologs does provide a d i v e r s e body of novel compounds to compare both models. Since these compounds were used i n the c o n s t r u c t i o n of the models, the performance should be b e t t e r than on a new t e s t s e t ; but s i n c e they were used i n both models one should o b t a i n a d i r e c t i n d i c a t i o n of any improvement. The t r a i n i n g set of A s , C's and N's minus analogs was combined and run through the same three v e r s i o n s of the model as a p p l i e d to t e s t set 2. The graph i n F i g u r e 1 shows the performance on a l l the a c t i v e s , as they rank among the N's. The A s and the C's are graphed s e p a r a t e l y . R e c a l l that the C's are more than ten times as numerous as the A's. Again, the 5A+C model was run before and a f t e r the m o d i f i c a t i o n f o r i n c i d e n c e . F i g u r e 1 shows a d e f i n i t e improvement on the novel compounds upon the removal of anologs. Although there are two b a s i c d i f f e r e n c e s i n the c o n s t r u c t i o n of the models, i . e., the A/C r a t i o , and the r e f e r e n c e i n c i d e n c e , the r e s u l t s are comparable f

1

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

596

Figure 1. Cumuhtive percent active for the training set without analogs vs. decile. Percentages are plotted at the lower end of each decile and joined linearly. ( ; A's; ( ) C's; (Q) original 2A - f C model; (Π) 5A + Canalogs; and (A) 5A + C-analogs with incidence modification.

Figure 2. The branching carbon atom yields exactly the same AA keys as the two structures shown, but different GAA keys (AA keys cannot distinguish carbon central atom in these structures; GAA keys can)

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

26.

HODES

Antitumor Drugs

597

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

because each model was s u i t e d to the c o n d i t i o n s under which i t was constructed. What i s most s u r p r i s i n g i s the e f f e c t of the i n c i d e n c e m o d i f i c a t i o n . By t h i s change, the f e a t u r e s whose weights are diminished are those most prevalent i n the t r a i n i n g s e t , so one would t h i n k these f e a t u r e s would have induced greater separation at t h e i r o r i g i n a l higher weight, at l e a s t on the training set. In order to achieve the improvement shown i n F i g u r e 1, t h i v e f f e c t must be more than balanced by the e f f e c t due to r e l a t i v e l y increased weight of low i n c i d e n c e f e a t u r e s . S u f f i c i e n t l y n o v e l compounds w i l l o f t e n have one or more low i n c i d e n c e f e a t u r e . I t was g r a t i f y i n g to see that t h i s i n f l u e n c e d enough compounds to outweigh the l o s s due to diminished weight of the high i n c i d e n c e f e a t u r e s even on the t r a i n i n g s e t .

The GAA

Model.

Thus f a r the f e a t u r e s used were as described i n (1). These are augmented atom (AA) keys and c e r t a i n kinds of r i n g keys. The AA keys c o n s i s t of a c e n t r a l atom, i t s bonds, and the neighboring atoms attached to the bonds. A l l combinations of attachments are permitted. There was a l s o a v a i l a b l e an a l t e r n a t e set of keys f o r searching which c o n s i s t s of f e a t u r e s s l i g h t l y l a r g e r than the AA keys. These were c a l l e d the g a n g l i a augmented atom (GAA) keys. They i n c l u d e the AA key and a l l the bonds attached to a l l the atoms. The GAA keys and not the AA keys are capable of d i s t i n g u i s h i n g the c e n t r a l carbon atom i n F i g u r e s 2a and 2b. Examination of some of the f a i l u r e s i n the preceeding models i n d i c a t e d that the GAA keys would improve performance, although there were other examples which were l e s s t r a c t a b l e . The easy a v a i l a b i l i t y of these f e a t u r e s became the determining f a c t o r i n d e c i d i n g to use them. To avoid questions of redundancy, the GAA keys were used i n place of the AA keys. The r e s u l t s on t e s t set 2 shown i n Table IX should be compared to Tables VII and V I I I . There appears to be a s i g n i f i c a n t improvement, e s p e c i a l l y i n the c e n t r a l column which l i s t s the t o t a l C r a t e d compounds.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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DESIGN

Table IX. Ranking of A c t i v e s i n Test Set 2. GAA Key 5A+C Model w i t h Incidence M o d i f i c a t i o n .

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

RANK (Deciles)

A COMPOUNDS NO. CUM.%

C COMPOUNDS NO. CUM.%

C NON-ANALOGS NO. CUM.%

10 9 8 7 6

19 1 1 3 2

58 61 64 73 79

60 25 11 9 13

40 57 64 70 79

20 14 4 3 6

29 50 56 60 69

5 4 3 2 1

0 4 2 1 0

91 97 100

11 7 5 4 5

86 91 94 97 100

8 5 2 4 2

81 88 91 97 100

The r e s u l t s on the t r a i n i n g s e t i t s e l f a r e compared w i t h the AA models i n F i g u r e 3. The GAA model i s 5A+C-analogs w i t h i n c i d e n c e m o d i f i c a t i o n , as i s the best AA model. On the t r a i n i n g s e t , the main improvement l i e s i n performance on the A's. The Rarest Key Report. Since the emphasis of the screening program remains the t e s t i n g of n o v e l compounds, a crude approximation to a measure of n o v e l t y was attempted. A program was w r i t t e n t o simply p r i n t o u t , f o r each compound i t s key which has l e a s t i n c i d e n c e i n P388 t e s t i n g and a l s o any new keys, which have not y e t appeared i n P388. The r a r e s t key a l s o shows s i g n i f i c a n t d i f f e r e n c e s i n switching from AA keys t o GAA keys as seen from the example i n F i g u r e 4. The r a r e s t AA key has occurred i n 107 compounds which have been t e s t e d i n P388, but the r a r e s t GAA key, with a d i f f e r e n t c e n t r a l atom, has occurred only once. Work i n Progress. O p e r a t i o n a l Model. During the past year an o p e r a t i o n a l model has been i n s t a l l e d a t Chemical A b s t r a c t S e r v i c e , where the NCI Chemical Information System i s maintained. T h i s model w i l l y i e l d r e p o r t s on a c t i v i t y score and r a r e s t key beginning A p r i l 1, 1979. The i n s t a l l e d model i s based on an extension of the t r a i n i n g set without analogs as d e s c r i b e d e a r l i e r . A search of the b i o l o g i c a l f i l e , NSC numbers 260001 and above, was performed May, 1978, followed by a machine search to remove analogs s i m i l a r to the search performed on the e a r l i e r t r a i n i n g s e t . The augmented t r a i n i n g set has the A s increased from 83 to 115, the C's from f

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

26.

HODES

Antitumor

599

Drugs

Figure 3. The performance of the GAA model on the same training set is shown in (Q) together with the graphs of Fig­ ure 1. Note that the 5A + C-analogs model is now represented by (Φ) instead

of(n).

IS THIS COMPOUND NOVEL?

NH—Me

NO - AA KEY 107 OCCURRENCES

oI

YES - GAA KEY 1 OCCURRENCE

Figure 4. The rarest key often turns out to be quite different in the AA key et from that of the GAA key set S

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

600

COMPUTER-ASSISTED

DRUG DESIGN

1182 to 1950 and the N's from 14357 to 33828. The model was run f i r s t w i t h AA, then w i t h GAA keys. At t h i s time a new v e r s i o n of the GAA key model was generated; here keys which had g a n g l i a on the c e n t r a l atom were e l i m i n a t e d . Thus o n l y the l a r g e s t GAA keys were kept. T h i s amounts to a decrease i n redundancy which i s e a s i e r to perform on the GAA than the AA keys. Performance was again compared by running the extended t r a i n i n g set through the r e s p e c t i v e models. The model u s i n g the l a r g e s t GAA key was d e c i d e d l y the b e s t , w i t h about 45% of the a c t i v e s i n the top 10%. A more a p p r o p r i a t e i n d i c a t i o n of performance would i n v o l v e s e t t i n g a s i d e ten or twenty percent cuts as t e s t s e t s . This i s being worked on now and w i l l be r e p o r t e d soon. The Test of 1000. An assortment of 1000 p o t e n t i a l a c q u i s i t i o n s was provided by Starks C. P., the a c q u i s i t i o n s c o n t r a c t o r as a t e s t of the model. These compounds were f i r s t reviewed by Ken P a u l l and were assigned on the b a s i s of t h e i r chemical s t r u c t u r e only to one of the f o l l o w i n g three c a t e g o r i e s : a c t i v e , n o v e l , or i n a c t i v e . Then they were run through the models at CAS. In a d d i t i o n , the e n t i r e 1000 have been put i n t o P388 testing. This experiment serves s e v e r a l purposes. I t was undertaken mainly to f a m i l i a r i z e Starks C. P. w i t h the model. A l s o , i t shows how unselected compounds rank against the NCI f i l e . I f one uses the s c a l e of the t r a i n i n g s e t , then 23-30 of the 1000 f a l l i n the highest d e c i l e and 350-500 i n the lowest d e c i l e , depending on the v e r s i o n of the model. Another purpose of the t e s t of 1000 i s to compare the r e l a t i v e performance of an experienced chemist w i t h the performance of the model, not to see which i s b e t t e r (undoubtedly the chemist) but to see i f t h e r e are some t h i n g s the model w i l l c a t c h which are not obvious to the chemist. In f a c t , review by the chemist of the 30 compounds which scored i n the top d e c i l e , l e d him to r e v i s e h i s o p i n i o n of a c t i v i t y from o r i g i n a l l y 15 to almost a l l , i . e., 28 as p o s s i b l y a c t i v e . A second chemist, Frank W i l l i a m s , performed the review. T h i s experiment should be completed i n about a year, when the P388 t e s t i n g i s f i n i s h e d . I t w i l l be r e p o r t e d at that time. Other S t r u c t u r e Features. In t h i s type of work, more s p e c i f i c f e a t u r e s tend to y i e l d b e t t e r r e s u l t s , as i s evidenced by the use of the GAA keys. With permission from the B a s e l Information Center f o r Chemistry (BASIC), we have been experimenting w i t h t h e i r keys on our data at CAS. The BASIC keys i n c l u d e l i n e a r sequences, which are chains of atoms of l e n g t h four to s i x w i t h bonds s p e c i f i e d only as to t h e i r r i n g or non-ring c h a r a c t e r . The BASIC has f o r some time been performing s u b s t r u c t u r e search on the e n t i r e CAS f i l e . Thus, BASIC keys are r o u t i n e l y generated i n l a r g e volume f o r compounds newly r e g i s t e r e d at CAS and can be used f o r s u r v e i l a n c e at low c o s t .

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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Performance on t e s t set 2 i s shown i n Table X. The A s and C's are combined i n these s t a t i s t i c s f o r a comparison of performance on a l l the a c t i v e s . So f a r the BASIC keys are not as d i s c r i m i n a t i n g as the NCI keys. Improvement was expected by the use of c o n d i t i o n a l p r o b a b i l i t i e s among l i n e a r sequences to cut down redundancy, but e a r l y r e s u l t s show no such improvement. T h i s i s being worked on by Paul Blower of CAS, who i s a l s o i n v e s t i g a t i n g the use of co-occurrences.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

Table X. Cumulative Percent A c t i v e i n Test Set 2. BASIC and NCI models. DECILE

BASIC

NCI-AA

NCI-GAA

10 9

30.5 40.1

33.9 45.8

43.5 58.7

Another set of s t r u c t u r e f e a t u r e s i s given by an a l g o r i t h m i c d e f i n i t i o n of a f u n c t i o n a l group. This i s e s s e n t i a l l y any connected subset of atoms which does not c o n t a i n a carbon-carbon s i n g l e bond or a carbon-carbon r i n g a l t e r n a t i n g bond. A program f o r generating such groups has been presented to the author by Paul Blower and t h i s w i l l be worked on soon. An i n t r i g u i n g combination would be l i n e a r sequences w i t h i n t e r n a l carbon atoms and f u n c t i o n a l groups. Summary. Current animal screening methods at the N a t i o n a l Cancer I n s t i t u t e i n c l u d e the use of a standard pre-screen (P388) to t e s t roughly 15,000 new compounds a year. R e s u l t s from P388 t e s t i n g have beeen used to c r e a t e an experimental s t r u c t u r e - a c t i v i t y model to a i d i n s e l e c t i n g compounds l i k e l y to be a c t i v e i n P388. In order to b e t t e r detect new l e a d s , well-known a c t i v e c l a s s e s of compounds have been e l i m i n a t e d from the t r a i n i n g data. There were s t i l l aproximately 1300 a c t i v e compounds and 14,000 i n a c t i v e s so that a s t a t i s t i c a l model f o r p r e d i c t i o n of a c t i v i t y was the method of c h o i c e . The p r e d i c t o r s are molecular s t r u c t u r e f e a t u r e s p r e v i o u s l y used i n searching the chemical s t r u c t u r e f i l e . The method assumes independence of f e a t u r e s , so new combinations can be e a s i l y detected. Emphasis on low i n c i d e n c e f e a t u r e s a l s o helps p o i n t toward n o v e l compounds. In t h i s v e i n , f o r each compound the f e a t u r e o c u r r i n g l e a s t o f t e n and a l l f e a t u r e s not yet i n P388 t e s t i n g are f l a g g e d . At t h i s time there i s some general agreement regarding the usefulness of the methods. The r e s u l t s on t e s t data are q u i t e encouraging, e s p e c i a l l y w i t h the GAA model. The methods are being put i n t o o p e r a t i o n a l use so more concrete r e s u l t s are expected.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

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602

Meanwhile, improvements are plannned f o r the models. Acknowledgement. Besides the people mentioned i n the paper I owe thanks to Sid Richman and Ruth Geran and s e v e r a l others a t NCI and CAS.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ch026

Literature Cited. 1. Hodes, Louis et al, J. Med. Chem., (1977), 20, 469. 2. Cramer, Richard D. et al, J . Med. Chem. (1974), 17, 533. 3. Richman, Sidney et al, in Retrieval of Medicinal Chemical Information, ACS Symposium Series, (1978). 4. Schenk, H.R. and Wegmuller, F . , J. Chem. Inf. Comput. Sci., (1976), 16, 153. RECEIVED

June

8, 1979.

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

INDEX

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ix001

A

A A k e y s (augmented atom) 585 Abinitio ( A I ) calculation of acetylcholine ( A C h ) 166 drug design 150,445 M O D P Ô T / V R D D O calculations on D N A bases 422 quantum chemical calculations 4,415-428 Absorption of acids, buccal 511, 512*, 514* colonic 508,510 studies 508 at various p H s, buccal 513 Acetates, acid hydrolysis of 35 Acetic acid 302 Acetylcholine ( A C h ) 301 ab initio calculation of 166 A C h E catalyzed hydrolysis of 302 acylation intermediates for 307*, 310* mechanism of 303 enzymic hydrolysis of 301-314 intermediates 306 P C I L O calculations of 166 valence energy for enzymic acylation of 305* Acetylcholinesterase ( A C h E ) 301 active site of 301 catalyzed hydrolysis of A C h 302 catalyzed hydrolysis of A S C h 302 N-Acetyl phenylalanyl tyrosine 90 crystal structure of 89 Acetylthiocholine ( A S C h ) 301 A C h E catalyzed hydrolysis of 302 acylation intermediates for 307*, 310* acylation mechanism of 303 enzymic hydrolysis of 301-314 intermediates 306 valence energy for enzymic acylation of 305* A C h (see Acetylcholine) A C h E (see Acetylcholinesterase) A S C h ( see Acetylthiocholine ) Active analog approach ( A A A ) ... 205-223 Active site-substrate complexes, computer-generated 192,194 Activity, biological 21 Activity relations, structure-^ SAR) 103-125 Acylation mechanism of A C h 303 Acylation mechanism of A S C h 303 Acyl enzyme 306 Adamantane(s) 155 analogues, structures and inhibitory activities of 157 -1-carboxylic acid 155

ADAPT computer software system descriptor manipulation routines in descriptors used for N-nitroso data descriptors used for P A H study environment descriptors in fragment descriptors in geometric descriptors in linear discriminant function in linear discriminant function analysis ( L D F A ) in molecular connectivity descriptors in N-nitroso compound study in nonparametric recognition programs in P A H study parametric pattern recognition programs in path and path environment descriptors in pattern recognition analysis in sigma charge descriptor in substructure descriptors in topological descriptors in training set/prediction set generation routine in variance feature selection in weight vector utility routine in Additivity postulate S-Adenosylmethionine S-Adenosylmethionine synthetase Adenylate cyclase A D H - N A D (see Alcohol-dehydrogenase-nicotinamide adenine dinucleotide ) Adrenergic agents, active Agonist(s) /antagonist potency receptor AI ( see ab initio ) ALCHEM Alcohol dehydrogenase, horse liver .... Alcohol-dehydrogenase-nicotinamide adenine dinucleotide ( A D H NAD) active site of complex with alkyl-substituted cyclohexanols, interaction of .... Alcohol dehydrogenase, stereoview of the active site of Algorithm in C A M S E Q , bond rotation Algorithm in C A M S E Q , geometry determination

605

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

106 112 124* 119* 109 109 112 115 114 109 122 114 120f 113 109 112 110 109 109 113 116 113 22 215 214 441

442 219 244 227 543 191

192 192 193/ 355 356

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ix001

606

COMPUTER-ASSISTED DRUG DESIGN

Aliphatic systems, i r constants from ... 29t Allosteric effects in enzymes 206 Alloxan 215,217,218/ Amine(s) biogenic 215 receptor, biogenic 221 sympathomimetic 439 structure-activity relationships (SAR) in 441 Amino acid residues of glycyl 407 Amino acid residues of valyl 407 2-Amino-6,7-dihydroxy-l,2,3,4-tetrahydronaphthalene ( 6 , 7 - A D T N ) .. 219 endo-2-Amino isomer of benzobicyclo [2.2.2] octene 459-481 exo-2-Amino isomer benzobicyclo [2.2.2] octene 459-481 γ-Aminobutyric acid 206 2-Aminononorbornane-2-carboxylic acid 214 Ammonium methylphosphate (AMP) 245/,246 complexes of 251-257,253/ H-bonded 248 Ammonium methylsulphate (AMS) 245/, 246 complexes 251-257,254/ H-bonded 248 A M P ( see Ammonium methylphosphate ) Amphetamine ( s ) 451, 459 analogs 478 decalin 454 C N D A / 2 calculations on 471 conformational energy map of 474/ energy surfaces for 472 endo-isomers of 459 exo-isomers of 459 A M S ( see Ammonium methylsulphate ) Analgesic(s) 94 activity, opiate 244 pharmacophore 221 structures, opiate 94 Anhydrobutaclamol 237 Anilines, dissociation of 33 Anionic receptor sites 244 model 245/ opiate 243-257 Anion interaction, cation— 246 Antagonist(s) 219 dopamine receptor 236 narcotic 417 opiate 243 potencies 255 agonist/ 244 and binding affinity of benzomorphans 252f receptor 227 H -Antagonist activity 181 2

Antibiotics, structure—activity rela­ tionships of tetracycline 142 Antitumor drugs for animal screen­ ing, computer-aided selection of 583-601 Antitumor screening program of the National Cancer Institute ( N C I ) 583 (-)-Amorphine 228 ARCANA 302, 313 calculations, orbital parameters in .. 314i Aromatic binding site 231 hydrocarbons, poly cyclic ( P A H ) .... I l l carcinogens 116 substitutions, electrophilic 33 systems, ττ constants from 29t N-Arylanthranilic acids 520 a-Aryl-a-cyanocarbonylphenylhydrazones 521 2-Aryl-l,3-indanediones 521 Atlas of Steroid Structure 81 Atomic charge densities 562 ATPase ( N a , K ) 441 inhibition data 272f-273i inhibition studies of genins 270 Augmented atom ( A A ) keys 585 +

+

Β Barbiturates 323/ commercial 322 Basel Information Center for Chemistry ( B A S I C ) 600 B A S I C ( Basel Information Center for Chemistry) 600 Bayesian classification surfaces 104 Bayesian theorem 113 Bacteriostatic action 152 of carboxylic acids 522 of nitrophenols 518i of phenols 517 1,4-Benzenediamine, synthesis of 344 7,8-Benzflavone 412/ Benzobicyclo [2.2.1] heptenes 459 Benzobicyclo [2.2.2] octene(s) 459 endo-2-amino isomer of 459-481 endo-2-methylamino isomer of ...459-481 exo-2-amino isomer of 459-481 exo-2-methylamino isomer of 459-481 system 459 Benzoic acids 32 Benzomorphans 243 antagonist potency and binding affinity of 252f Bicyclic ring structures, ring strain in the 464 Bicyclic systems, C N D O / 2 calcula­ tions on 476 Binding interactions 197 sites 214

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ix001

INDEX

607

Binding (continued) sites (continued) aromatic 231 on dopamine receptor lipophilic accessory 238/ primary 235/, 238/ lipophilic accessory 237 opiate 243 primary 228 substrate 320 Bioactive synthesis 319-339 binding parameters in 320 reaction parameters in 320 transport parameters in 320 Biodata 320 Bioenergetic models 320 Bioisosterism 207 Biological activity 21, 39 influence of electronic effects on .... 40 influence of steric effects on 45 relations using pattern recognition, chemical structure103-125 Biologically active compounds, design of 383-413 Biologically active substance, conformationally-restricted analogs of a 454 Biological mechanisms, theoretical models for 165 potency of a drug 67 systems, interaction of drugs with .. 53 Biomolecular interactions 161 Bocek-Kopecky interaction model .... 64 Bond angle deformation energy 84 distance deformation energy 84 formation, hydrogen 234 length shortening, thermal 82 overlap population 309 rotation algorithm in C A M S E Q 355 Boronate derivatives 199 Boronate inhibitor to subtilisin, stereoview of 202/ Brain membranes, L S D binding to .... 177 B. subtilis by carboxylic acids, inhibition of 525i Buccal absorption 5l4t of acids 511 of organic acids 512f at various pH's 513 Butaclamol 219,227-239 enantiomers of 228 ( + )-Butaclamol 228 conformers, Dreiding models of nuclei of 232/ hydrobromide 231 crystal structure of 230/

C Cambridge Crystallographic Data Centre

81

CAMSEQ batch 364 bond rotation algorithm in 355 geometry determination algorithms in 356 potential functions in 356 Software System 353 CAMSEQ-II 356,562 C A M S E Q / M ( Microprocessor-Based Conformational Analysis System) 353-369 computer hardware for 357 data analysis options 366 graphics model builder in 359, 360/ isoenergy contour maps ( C M A P S ) in 366 structure of phenethylamine by 360/ Cancer Institute ( N C I ) , antitumor screening program of the National 583 Carbaldoximes, configurational analysis, inversion and reduction of pyridine 489-501 Carbonium ion metabolites of cyclic nitrosamines, role of 580 Carbonium ion metabolites of nitrosamines 564 Carboxylic acids bacteriostatic activity of 522 inhibition of B. subtilis by 525i 2-Carboxy-nitrosopyrrolidine 571 Carboxypeptidase 53 active site of 173/ enzymatic mechanisms in 165 mechanism of action of 172 molecular electrostatic potential of the active site of 174/ Carcinogenic activity 105 nitrosamines 105 data base, hierarchal Q S A R molecular structure calculator applied to a 553-580 potency 116, 553, 578 of a compound 554 Carcinogens 105 polycyclic aromatic hydrocarbon (PAH) 116 Cardenolide(s) backbones, saturated 262 8(14)-ene D-ring structure of ...265,267 14-ene D-ring structures of 265, 267 energy diagrams of 267 functional receptor mapping for modified 259-277 genins 260 saturated D-ring structures of 265 17/?-side group orientation of 265 structural studies 260 toxicity 259

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

COMPUTER-ASSISTED DRUG DESIGN

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ix001

608 Catalytic activity 165 Catecholamines 458, 467 Cation-anion interaction 246 Cell membranes, phenol inhibition of chloride passage across 519 Chance correlations 131 Charge densities, atomic 562 Charge transfer interactions 246 Chemical Abstract Service 598 Chemical Information System ( CIS ) NIH-EPA356 Chemical reactivity 163 Chemical searches, computer-based .. 155 Chemical structure-biological activity relations using pattern recognition 103-125 Chirality 234 Chloride passage across red cell membranes, phenol inhibition of 519 Chloromethylketones 201 peptide 199 p-Chloro-phenoxyacetic ester 373 Chlorpromazine 210/ conformers of 221,222/ phenothiazine neuroleptic 211 a3OH-50cholanic acid, stereoview of model of 195/ /?30H-5/?cholanoic acid, steroview of model of 195/ Choline 302, 306 Chorismate 155 Chorismate mutase, inhibition of 152 Chorismate mutase-prephenate dehydrogenase 154 Chorismate to prephenate, Claisen rearrangement of 152 Chorismate to prephenate, isomerization of 153 Chronotropic activity 259 Chymotrypsin, enzymatic mechanisms in 165 Cimetidine 181 CIS (Chemical Information System), NIH-EPA356 Claisen rearrangement of chorismate to prephenate 152 Classification surfaces, Bayesian 104 CLINORIL 538 synthesis of 539 Clofibrate 373 chemical structures of 375/ Clonidine, Q S A R in centrally acting imidazolines structurally related to 143 Cluster analysis 571, 578 C M APS ( isoenergy contour maps ) inCAMSEQ/M 366 C N D O (see Complete Neglect of Differential Overlap )

Cocaine 441 Collanders equation 31,32 Colonic absorption 508 of acids and bases 510f Complete Neglect of Differential Overlap ( C N D O ) 445 calculations on amphetamines 471 on bicyclic systems 476 and X-ray crystallographic analysis to the design of conf ormationally defined analogs of methamphetamine 439-481 method 564 wave functions 427 Computer -aided design of inhibitors 194 design of substrates 194 selection of antitumor drugs for animal screening 583-601 -assisted synthesis 321 -assisted synthetic analysis 527-549 -based chemical searches 155 -controlled diffractometers 81 -generated active site-substrate complexes 194 graphic(s) 99,384 interactive 189 graphic techniques for molecular manipulations 151 hardware 190 for C A M S E Q / M 357 program synthesis of Depoprovera proposed by 345/ syntheses of drugs by a 341-352 synthesis of P G F « proposed by .. 347/ software 190 system, A D A P T 106 system, N I H P R O P H E T 260 Computing systems, crystallographic 81 Comsub Data 338 Configuration interaction calculations 424 Conformation-activity relationships .. 166 Conformation(s) 166 analysis of module M O L Y (CONFOR) 386 crystal 87 energy 387 molecular 84 receptor-bound 205 receptor-site 231 Conformational analysis 383-413 in drug design, applications of .... 367 module in M O L Y , parameterization of the 390 in molecular modeling, applications of 367 2

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

609

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ix001

INDEX Conformational (continued) characteristics of molecules 9 hyperspace 366 parameter in drug design 205-223 search, systematic 209 studies of phenylethylamines 445 Conformationally-defined phenyl­ ethylamines 471 Conformationally-restricted analogs of a biologically active substance ... 454 C O N F O R ( Conformation analysis module of M O L Y ) 386 comparison of P C I L O and 390 Conjugation 388 Connectivity indices 36 π Constants from aliphatic systems .... 29i π Constants from aromatic systems .... 29t Correlation equations 131 Coulombic interactions 192 Coulomb's law-type function 354 Crystallographic computing systems .. 81 Crystallography, x-ray 443 Crystal conformation 87 structure of N-acetyl-phenylalanyl tyrosine 89 analysis in drug design 79-100 thermal vibration in 82 Cyclohexanols, interaction of A D H N A D complex with alkyl-substituted 192 Cysteine proteinase 11 Cytochrome P-450 564

D Data base hierarchal QSAR molecular struc­ ture calculator applied to a carcinogenic nitrosamine ... 553-580 for multiple regression 321 on-line 341 Data storage 543 Deamino acids 286 Decalin amphetamine analogs 454 Decalin compounds, trans454 Deformation energy bond angle 84 bond distance 84 out-of-plane 85 Dehydrogenases 327 fungicides inhibiting 328/ Del Re sigma charge calculation 110 Density map, pseudoelection 214 Depoprovera 344 proposed by computer program, synthesis of 345/ Descriptors in A D A P T environment 109 fragment 109

Descriptors ( continued ) in A D A P T (continued) geometric 112 manipulation routines in A D A P T 112 molecular connectivity 109 path and path environment 109 sigma charge 110 substructure 109 topological 109 electronic 110 group additive molecular 554 molecular mechanics 555 substructure 584 used for N-nitroso data, A D A P T ... 124f used for P A H study, A D A P T 119* quantum mechanical 562 Desipramine 441, 479 Desoxybutaclamol 237 Diastereoisomers 125 5,11-Diazaditwistanes 541 exo-3-Dicarboxylic acid 156 Differential solvation approach 168 Diffractometers, computer-controlled 81 Digitalis 259 genin-Na ,K -ATPase inhibition 258-277 glycosides 259 receptor 259 Digitoxigenin 259-277 molecular structure of 261/ Digitoxin 260 Dimaprit 181 Dimethyl 2'hydroxy 6,7 benzomorphan analogues, N-substituted 5,9 255 2',3 -Dimethyl-3,5-diiodothyronine ... 283 2 ,5 -Dimethyl-3,5-diiodothyronine .... 283 Dinucleoside monophosphate ( C p G ) crystalline complex, ethidium/ .... 358/ Diphenyl methane structure, genera­ tion of 362 Dispersion-type interaction 246 Dissociation, process of 59 DNA bases, ab initio M O D P O T / V R D D O calculations on 422 double helix 12 -drug models 12 -hydrocarbon binding 122 intercalator 12 H-Dopamine ( D A ) 478 Dopamine receptor 215,227-239 antagonists 236 lipophilic accessory binding site on 238/ model of 238/ primary binding sites on 235/, 238/ Double helix, D N A 12 +

+

r

/

/

3

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ix001

610

COMPUTER-ASSISTED DRUG DESIGN

Dreiding models of nuclei of ( + )butaclamol conformers 232/ Dreiding models of nuclei of ( + )isobutaclamol conformers 232/ Drug action 4 equation 568 molecular determinants for 169 activity 169 for animal screening, computeraided selection of antitumor 583-601 biological potency of a 67 with biological systems, interaction of 53 by a computer program, syntheses of 341-352 conformation, solvent effects on 168 design 3 ab initio 150 applications of conformational analysis in 367 conformational parameter in .205-223 crystal structure analysis in 79-100 molecular mechanics in 79-100 quantum mechanical methods in 60 distribution phenomena 59 intercalation 12 models, D N A 12 reactive sites of 169 -receptor interactions 161 activation in 175 quantum chemical recognition mechanisms in 161-183 quantum chemical studies on 169 recognition i n 175 schematic 210/ specificity in 54 receptor site 190

Ε E H T (Extended Huckel Theory) 445 Electron density fitting in protein crystallography 214 Electronic charge distribution 44 descriptor 110 effects 39,59 on biological activity, influence of 40 substituent constants for 23 factors in Q S A R using distribution coefficients 507-526 mechanisms in substrate—enzyme interactions 175 properties of nitrosamines 125 substituent constant 40 Electrophilic aromatic substitutions .. 33 Electrostatic interactions 85, 354 molecular potential 374

Electrostatic ( continued ) contour maps 427 energy contours of the 374 potential of the active site of carboxypeptidase, molecular 174/ field 170 of 5-hydroxytryptamine, molecu­ lar 180/ of D - L S D 180/ maps 9 of 5-hydroxytryptamine 178 of L S D 178 molecular 170 Ellipticines 586 Enkephalin 221 Enthalpy 42 Entropy 42 Enantiomers of butaclamol 228 Enantiospecificity 228 Energy bond angle deformation 84 bond distance deformation 84 calculations of opiates, empirical potential 243-257 calculations of opiates, P C I L O potential 243-257 of complex formation, intermolecular 246 conformation 387 contours of the electrostatic molecular potential 374 decomposition, S C F 426 diagrams of cardenolides 267 electrostatic interaction 85 free 28,87 function, classical-type empirical potential 355 nonbonded interaction 84 out-of-plane deformation 85 solvation 168 strain 84,85,87,108 total interaction 247 total overlap 311 valence 304 Enzymatic mechanisms in carboxypeptidase 165 Enzymatic mechanisms in chymotrypsin 165 Enzyme(s) acyl 306 allosteric effects in 206 inhibitors 149 structure—activity studies of 194 Enzyme-substrate complex 168 Enzyme—substrate interactions 10 Ephedrine 394 conformations of 451 energy contours for 403/

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

611

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ix001

INDEX Esophagus, tumors of the 554 Ethidium 12 Ethidium/dinucleoside monophosphate ( C p g ) crysatlline complex 358/ N-Ethylamphetamine 476 conformational energy map of 475/ energy surfaces for 472 E X B I O C O R (Extrapolated Biocorrelation Program) 336 Excluded volume map 214 Extended Hiickel Theory ( E H T ) 445 Extrapolated Biocorrelation Program (EXBIOCOR) 336 Extrathermodynamic derivation of Q S A R parameters 22 Extrathermodynamic parameters 61 Extrathermodynamic relationships ... 21

GIPSY ( Gaussian Integral Program System) 418 Globular proteins, glycyl residues in.. 407 D-glucose 215 Glucose receptor 215 Glycosides, digitalis 259 Glycyl amino acid residues 407 residue, energy contours for 408/ residues in globular proteins 407 Graphics model builder in CAMSEQ/M 360/ Graphics model builder option in CAMSEQ/M 359 Graphics system, M M S - X 214 Guanidines 496

F

H

Fentanyl citrate 83 conformations of 98 molecule 94 F I T M O L , P R O P H E T procedure 270 Flavin coenzymes 165 5-Fluorouracil 586 Fock matrix elements 424 Formamide 175 FORTRAN 386,531 Multiple Regression Analysis Program 132 Free energy 28 Free-Wilson method for Q S A R 63 Frontier densities 177 Functional groups 163 Functions, mathematical form of potential 389i Function, nonbonded potential ... 395t-400f Fundus, rat 177 Fungicidal activity 330 Fungicides 327 inhibiting dehydrogenases 328/ Furan compounds 247

G G A A ( ganglia augmented atom ) 585 G A A ( ganglia augmented atom ) keys 597 Ganglia augmented atom ( G A A ) 585 Ganglia augmented atom ( G A A ) keys 597 Gaussian integral programs 418 Gaussian Integral Program System (GIPSY) 418 Genin(s) 259 cardenolide 260 Na ,K -ATPase inhibition studies of 270 Geometry determination algorithm in C A M S E Q 356 Geometry optimization, intermolecular 251 +

+

Hallucinogens, action of 169 Hammett equation 23 Hammett parameters 23 Hansch methods for Q S A R 62 Hansch equation 320 Hardware for C A M S E Q / M computer 357 Hartree-Fock approximation 446 Herbicidal ureas 332/ Herbicides, thiolcarbamate 325, 326/ Herbicides, urea 331 Jrans-Hexahydrocarbazole 219 Hexanoic acid-4-aza-4-methyl-6-( 3pyrrolyl)-N,iV-diethylamide 181 Hexanoic acid-4-aza-4,5-dimethyl-6(3-indolyl)-N,N-diethylamide .... 181 Hexapeptide, stereoview of model of 198/ Hexoses 215, 217/, 218/ Highest Occupied Molecular Orbitals (HOMO) 177,178 Hildebrand-Scott solubility parameter 38 H i l l reaction 331 inhibition, Q S A R in 142 inhibitors 332/ Histimine 181 H -receptors 181 Histidine 199 H O M O (Highest Occupied Molecular Orbits) 177,178 Hormones peptide 212 thyroid 281,282/ cisoid/transoid conformation of .. 283 diphenyl ether conformation of .. 286 distal/proximal 3'-substituents of 283 and metabolites 294f protein binding characteristics of 292 -receptor interactions, binding models 281-297 Horse liver alcohol dehydrogenase .... 191 2

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ix001

612

COMPUTER-ASSISTED DRUG DESIGN

Huckel calculations, extended 415 method 313 molecular orbital calculations 374 Theory, Extended ( E H T ) 445 Hydrocarbon binding, D N A 122 Hydrocarbon ( P A H ) carcinogens, poly cyclic aromatic 116 Hydrocarbons, polycyclic aromatic .... I l l Hydrogen bond formation 234 -bonding effect 354 bonding sites 170 Hydrophilic molecules 57 Hydrophobic binding 57 effect(s) 39,53 interaction(s) 38 model 53 substituent constant 38, 50, 59 Hydrophobicity 112,161 6-Hy droxy adamantane- 1,3-dicarboxylic acid 154,156 exo-6-Hydroxybicyclo [3.3.1] nonane-1 156 exo-6-Hydroxybicyclo [3.3.1] nonane1, endo-3-dicarboxylic acid 154,156 exo-6-Hydroxybicyclo [3.3.1] nonane1, exo-3-dicarboxylic acid 154,156 3a-Hydroxy-5/?-cholanoic acid 194 3/?-Hydroxy-5j3-cholanoic acid 192 α-Hydroxy fatty acids 522 5-Hydroxytryptamine ( 5 - H T ) 163,177 electrostatic potential maps of 178 molecular electrostatic potential of 180/ Hyperconjugation constant 46 Hypolipidemic agent 373

Inotropic activity 259 Insulin release 215,217/ Interaction Field Modified Hamil­ tonian method ( I F M H ) 172 Interaction pharmacophore 170,171 of L S D 178 syn-anti Interconversion in oximes 497/ Intermediate Neglect of Differential Overlap ( I N D O ) 445 wave functions 427 Intermolecular interactions 52 Intramolecular interactions 51 Iodines, diortho 281 5-Iodocytidylyl (3'-5') guanosine 12 Ionophores 515 Iodothyronines 286 5-Iodouridylyl (3'-5') adenosine 12 Ionization fraction 58 ( + )-Isobutaclamol 228 conformers, Dreiding models of nuclei of 232/ hydrobromide 229,231 crystal structure of 230/ Isoenergy contour maps ( C M A P S ) in C A M S E Q / M 366 Isokinetic relationship 42 Isolipophilic groups 321 Isolipophilic thiolcarbamate 332 Isomers, optical 47

I

Langerhans, islets of 215 L C A O ( Linear combination of atomic orbitals) 61 L C A O - M O - S C F calculations 415 L E M O ( Lowest energy empty molecular orbital) 308 Lennard-Jones 6-12 potential 390,391/ functions 353 Leukemia, P388 mouse lymphocytic .. 583 Ligand complexes, receptor227 Linear combination of atomic orbitals (LCAO) 61 discriminant function in A D A P T .... 115 discriminant function analysis ( L D F A ) in A D A P T 114 regression analysis 571 L I N P L O T ( Linear energy vs. rotation angle plots) 366 Lipophilic accessory binding site 237 on dopamine receptor 238/ Lipophilic molecules 57

I B M R A N D U subroutine 132 I F M H method (Interaction Field Modified Hamiltonian) 172 Imidazol 302,304 Imidazolines structurally related to clonidine, Q S A R in centrally acting 143 Imidazolium 304 Incumbrance area 122 Indicator variables 65 Indole derivatives 177 Indoles, methylated 177 I N D O (see Intermediate Neglect of Differential Overlap ) 445 Inductive effects 27,34 Inductive substituent constants 35 Inhibitors computer-aided design of 194 enzyme 149 SH 328

Κ K -ATPase inhibition studies of genins, N a +

+

270

L

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

INDEX

613

LSD binding to brain membranes discriminant molecular determinants for the actions of electrostatic potential maps of interaction pharmacophore of reactive sites in D - L S D , molecular electrostatic potential of D - L S D molecular structures of Lysine

169 177 178 178 178 177 180/ 182/ 197

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ix001

M Macrodeformations 10 Macromolecular modeling 190 r>Mannose 215 Map, excluded volume 214 Mapping, receptor 227 for modified cardenolides, functional 259-277 Master Data parameter table 319-339 Mechanics, molecular 84 Mechanics, statistical 9 Membranes 56 Meperidine 10 hydrobromide 97 hydrochloride 97 Mercks, implementation of S E C S at .. 528 M E R G E option 423 Mescaline hydrobromide 445 Mesomeric effect 27 Methamphetamine 459 analogs 478 application of C N D O / 2 calculations and x-ray crystallographic analysis to the design of conf ormationally defined analogs of 439-481 endo-isomers of 459 exo-isomers of 459 Methanol 302 Methionine 214 Methylation, biological 215 Methylcyclopropyl compounds 247 N-Methyl-2-pyridiniumaldoxime (2-PAM) 489 Methyl cis-4-f-butyl cyclohexane carboxylates 47 Methyl £rans-4-i-butyl cyclohexane carboxylates 47 1- Methyl-2-pyridinium carbaldoxime isomers 500f 2- Methylamino-l,2,3,4-tetrahydro1,4-ethanonaphthalene hydrochlorides 463 2-Methylnitrosopiperidine 564 mechanism of metabolic activation of 565/ 4-Methyl-N-nitrosopiperidine 125

6- a-Methyl-17-«-acetoxyprogesterone.. 344 5-Methyl benz(a)anthracene 116 12-Methyl benz(a)anthracenes Ill 7- a- Methyl-19 lnorandrostenediol (7-a-Me) 80,89 anii-l-Methyl-l,4-dihydropyridine2-carbaldoxime 502/ flnii-l-Methyl-l,4-dihydropyridine2-carbaldozime ion, N-protonated 505/ anti-1- Methyl- 1,6-dihy dropyridine2-carbaldoxime 503f anii-l-Methyl-3,6-dihydropyridine2-carbaldoxime, C-protonated .... 503f anii-l-Methyl-5,6-dihydropyridine2-carbaldoxime ion, C-protonated 504/ anfi-l-Methyl-2-pyridiniumcarbaldoxime 494/ en(2o-2-Methylamino isomer of benzobicyclo [2.2.2] octene 459-481 exo-2-Methylamino isomer of benzobicyclo [2.2.2] octene 459-481 st/n-l-Methyl-2-pyridiniumcarbaldoxime 495/ Metiamide 181 Michael addition 328 activators 329/ Michael reaction, intramolecular 542 Michaealis complex 301 Microdeformations 10 Mimetics 372,374 MIMETIC-GEMO 372 M I N D O / 3 molecular orbital calculations 150,153 M I N D O / 3 S C F M O program 490 Minimal steric difference ( M S D ) 37 Mitochondrial monoamine oxidase (MAO) 441 Mitochondrial protein, binding of phenols to 519 Molecular basis of structure-activity relationships 161-183 conformations 84,166 descriptors, group additive 554 determinants for drug action 169 electrostatic potential map 170 geometries 372 interactions 425 perturbation procedures for 425 three dimensional specificity of .. 371 manipulation and superimposition.. 151 mechanics 84 descriptors 555 in drug design 79-100 modeling 108 applications of conformational analysis in 367 interactive 189 of site-specific pharmacophores .. 190

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ix001

614

COMPUTER-ASSISTED DRUG DESIGN

Molecular ( continued ) orbital calculations 149, 445 Huckel 374 on Large Systems (MOLASYS) 418 MINDO/3 153 semiempirical 302 lowest energy empty ( L E M O ) .. 308 M O S E S program 416 potential, energy contours of the electrostatic 374,427 reactivity 60 recognition 205 structure calculator applied to a carcinogenic nitrosamine data base, hierarchal Q S A R 553-580 structure, theoretical calculations on 167 substructure descriptors 584 wavefunction 61 Molecules, conformational charac­ teristics of 9 M O D P O T (model potential) 419 / V R D D O calculations on D N A bases, ab initio 422 Molar attraction constant 38 Molar refractivity 38 M O L A S Y S ( Molecular Orbital Cal­ culations on Large Systems) 418 MOLMEC 108 M O L Y program 384 architecture of 385/ conformation analysis module of (CONFOR) 386,395 M O S E S program ( Molecular orbitals ) 416 Monte Carlo approach 168 Morphinans 243 Morphine 9,243 molecule 94 monohydrate 88, 90 structure and atom numbering 8/ M S D (Minimal steric difference) 37 MULFIT 568 Mulliken net atomic charges 306 Multiple linear regression analysis in QSAR 66 perturbation expansion 178 regression analysis 131, 133 Multiplicative Congruential Method .. 132 Muscimol 213/

Ν Na ,K -ATPase enzyme inhibition data inhibition studies of genins +

+

441 259 272f-273i 270

Naloxone 243 Narcotic(s) 417 antagonists 417 opiate 243 National Cancer Institute ( N C I ) , antitumor screening program of the 583 N C I (National Cancer Institute), antitumor screening program of the 583 Nerve ending, noradrenergic 440/ Neuroleptic s ) 219,417 activity 219 pharmacophore 221 Neuronal transmitter 441 Neurotransmitter(s) 442 receptors for 227 NIH-EPA-Chemical Information System (CIS) 356 N I H P R O P H E T computer system 260 Ninhydrin 215, 217/ Nitrophenols, bacteriostatic activity of 518f Nitrosamine ( s ) 553, 556f-560f action model for cyclic 575 bioactivation 125 carbonium ion metabolites of 564 carcinogenic 105 cyclic 554 data base, hierarchal QSAR mo­ lecular structure calculator ap­ plied to a carcinogenic 553-580 electronic properties of 125 partition coefficients of 125 role of carbonium ion metabolites of cyclic 580 used in action model QSAR, cyclic 576i N-Nitroso compounds 123i N-Nitroso compound study in ADAPT 122 N-Nitroso data, A D A P T descriptors used for 124f Nitrosopiperidine 563/ conformers of 562 Nitrosopyrrolidines 562 N M R (Nuclear magnetic resonance) 447 Nonbonded interaction energy 84 19-Nor (19-Norandrostenediol) 80,89 Noradrenergic synapse 439 Noradrenergic nerve ending 440/ 19-Norandrostenediol (19-Nor) 80,89 Norephedrine 394, 406/ energy contours for 404/ Norepinephrine 439 ^-Norepinephrine ( N E ) 478 Nuclear Magnetic Resonance ( N M R ) 447 Nuclear proteins 293 Nucleophilic reactions 46 Nucleotide-serotonin complex 163

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

615

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ix001

INDEX

Octanol/water partition coefficients .. 55 Octoclothepin 219 ( + )-Octoclothepin 228 Opiate(s) analgesic activity 244 structures 94 anionic receptor sites, model 243-257 antagonist 243 binding site 243 empirical potential energy calcu­ lations of 243-257 fused-ring 244 narcotics 243 P C I L O potential energy calcu­ lations of 243-257 protonated amine in 246 receptor 243 —receptor interactions 9 modeling 243-257 rigid 9,243-257 N-substituents, PCILO-calculated energies in Η-bonded com­ plexes of 249f N-substituents, PCILO-calculated energies in complexes of 250£ N-substituents in rigid 244 Optical isomers 47 Organic synthesis, software develop­ ment for 341-352 Orientation map 207 Oripavines/thebaines 243 Ortho effect 47 Oxidative phosphorylation, uncou­ pling of 520 Oximes 498f-499t syn-anti interconversion of 496, 497/ Oxygen, formation of the activated ... 165 Oxyheme geometry 165

P A H (see Polycyclic aromatic hydro­ carbon ) 2 - P A M ( N-methyl-2-pyridiniumaldoxime) 489 reduction of 496 syn and anti forms of 493 Pancreatic trypsin inhibitor ( P T I ) .... 194 Papain 11 Parachor 38 Parathion 337

Pargyline-treated rat atria 479 Partition 53 coefficients 27, 50, 59 estimation Ill membrane/buffer 55 of nitrosamines 125 octanol/water 55 water/octanol 553 process of 59 Pattern recognition analysis in A D A P T 112 chemical structure-biological activity relations using 103—125 programs in A D A P T , nonparametric 114 programs in A D A P T , parametric .... 113 in Q S A R 62 SAR applications of 104 techniques 107/ P C I L O ( see Perturbative Configura­ tion using Localized Orbitals ) Peptide bond, sissile 194 chloromethylketones 199 hormones » 212 Perturbative Configuration Interaction using Localized Orbitals (PCILO) 246,394,445 -calculated energies in H-bonded complexes of opiate N-substitu­ ents 249f -calculated energies in η - » π com­ plexes of opiate N-substituents 250f calculations of acetylcholine 166 and C O N F O R , comparison of 390 contour maps 394 potential energy calculations of opiates 243-257 P G F « , syntheses of 346 proposed by computer program 347/ Pharmacologicals, theoretical studies on 5f—7t Pharmacology, quantum 3-12 Pharmacophore( s ) 205-223, 371 analgesic 221 chiral 228 interaction 170,171 of L S D , interaction 178 molecular modeling of site-specific 190 neuroleptic 221 Phosphorylation, uncoupling oxi­ dative 515,520 Physicochemical properties, predic­ tion of 164 Phenethylamine 394 by C A M S E Q / M , structure of 360/ derivatives 367 energy contours for 401/ moiety 236 2

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616

COMPUTER-ASSISTED DRUG DESIGN

Phenols activities of 515 bacteriostatic activity of 517 dissociation of 33 inhibition of chloride passage across red cell membranes 519 to mitochondrial protein, binding of 519 Phenothiazine neuroleptic chlorpromazine 211 Phenylacetic esters 32 Phenylethylamines 443, 447 analogs, bicyclic 463 conformationally-defined 459, 471 analogs of 462/ conformation studies of 445 Newman projections of 450/ solid state conformations of 443 x-ray studies of 467 2-Phenylethylamine 444/ Phenylethylanolamines 447 Phenylpropylamine moiety 229 2-Phenyl-l,3-indanediones 523* Platinums 586 P L / 1 program 323 Polar effects 25 Polycyclic aromatic hydrocarbon (PAH) 117* carcinogens 116 study, A D A P T 120/ descriptors used for 119* Potential energy calculations of opiates, empirical 243-257 calculations of opiates, P C I L O .243-257 contour maps, electrostatic molecular 170, 427 functions in C A M S E Q 356 classical-type empirical 355 Lennard-Jones 6-12 353,391/ mathematical form of 389* nonbonded 395*-400* parameters 84, 88 surfaces 168 Prephenate, Claisen rearrangement of chorismate to 152 Prephenate, isomerization of chorismate to 153 Progesterone 344 Program F I T 190 P R O P H E T procedure F I T M O L 270 P R O P H E T system 259-277 Prostaglandin structure 346 Prostaglandin synthetase, inhibition of 521,523* Proteases, serine 191,194 Protein(s) 56 binding characteristics of thyroid hormones 292

Protein(s) (continued) binding (continued) of phenols to mitochondrial 519 serum 283 structural features for optimal ... 295* thyroid 294* crystallography, electron density fitting in 214 Data Bank 190 glycyl residues in globular 407 nuclear 293 -protein interaction 53,161 receptor 292 serum 293 thyroid-binding 294* Proteinase, cysteine 11 Pseudoephedrine, conformations of .... 451 Pseudopotential theory 9 Pseudoprocaine 394 Pseudoprocrine, energy contours for .. 402/ Pyridinenealdoximes 489 Pyridine-2-aldoximes 490,496 Pyridine carbaldoximes, configurational analysis, inversion and reduction of 489-501 Pyridine, reduction of 500 2-Pyridinealdoxime 501 an*t-2-Pyridinecarbaldoxime 491/, 492/ syn-2-Pyridinecarbaldoxime 491/ Pyridinium aldoximes 493* Pyrimidinones, Q S A R in 142 Q Quinazolinones, substituted 30 Quinolizine system 231 Quadrone 542 Quantitative structure—activity relationships ( Q S A R ) 21-68,161,177, 205, 292, 319, 553 in centrally acting imidazolines structurally related to clonidine 143 cluster analysis in 62 cyclic nitrosamines used in action model 576* discriminant analysis in 62 Free-Wilson method for 63 Hansch method for 62 in H i l l reaction inhibition 142 -independent of an action model . . . 569 methods in 62 molecular structure calculator applied to a carcinogenic nitrosamine data base, hierarchal... 553-580 molecular structure calculator, hierarchal 554 multiple linear regression analysis in 66 parameters 32 extrathermodynamic derivation of 22 physicochemical basis of 39

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Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ix001

INDEX Quantitative structure-activity relationships ( Q S A R ) (continued) pattern recognition in 62 in pyrimidinones 142 quantum mechanical indices of reactivity in 61 quantum mechanical parameters in 60 statistical methods in 66 studies, chance factor in 131-145 -using an action model 575 using distribution coefficients, electronic factors in 507-526 Quantum chemical recognition mechanisms in drug-receptor interactions ...161-183 chemical studies on drug-receptor interactions 169 chemistry 60 Chemistry Program Exchange 150 mechanical descriptors 562 indices of reactivity in Q S A R 61 methods 164 in drug design 60 semiempirical 35 parameters in Q S A R 60 techniques, ab initio 4 pharmacology 3-12 Q S A R ( see Quantitative StructureActivity Relationships ) R

Random number generator 132 R A N D U subroutine, I B M 132 R A N G E Program 321, 327, 331, 335 modifiers 324/ Reaction(s) building 342 coordinate 150 facilitating 342 pathways 150 Reactive sites of drugs 169 Receptor agonists 227 antagonists 227 dopamine 236 -binding assays 223 biogenic amine 221 -bound conformation 205 digitalis 259 dopamine 215,227-239 essential volume 215 glucose 215 interactions binding models thyroid hormones281-297 modeling opiate 243-257 opiate9 specificity in d r u g 54

Receptor (continued) -ligand complexes 227 lipophilic accessory binding site on dopamine 238/ mapping 227, 369 for modified cardenolides, functional 259-277 model 99 of dopamine 238/ for neurotransmitters 227 opiate 243 primary binding sites on dopamine 235/, 238/ protein 292 recognition 161 -site conformations 231 sites anionic 244 model anionic 245/ model opiate anionic 243-257 and substrate interactions, modeling 189-201 Regression analysis, linear 571 Regression, data base for multiple 321 Reserpine-treated rat atria 479 Resonance effects 27,34 Ribonuclease A 206 Ribonuclease S 206 Ring strain in the bicyclic ring structures 464 Routine in A D A P T , training set/prediction set generation 113 Routine in A D A P T , weight vector utility 113 S SA (Serum albumin) 281 SAR (Structure-activity relations) 103-125 S C F energy decomposition 426 S E C S at Merck, implementation of ... 528 S E C S program modules 530* S E C S (Simulation and Evaluation of Chemical Synthesis) program .... 527 Separability postulate 23 Serine proteases 191,194 Serum albumin ( S A ) 281 Serum proteins 293 binding 283 S H inhibitors 328 Sigma charge calculation 110 D e l Re 110 Simulation and Evaluation of Chemical Synthesis ( S E C S ) program .. 527 Sissile peptide bond 194 Software development for organic synthesis 341-352 Solubility parameter, HildebrandScott 38 Solubility of water in apolar solvents .. 55*

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COMPUTER-ASSISTED DRUG DESIGN

439 Solute-solvent interactions 43 Sympathomimetic amines structure—activity relationship molecular changes in 44 (SAR) in 441 Solution theory 38, 52 439 Solvation effects 355 Synapse, noradrenergic Synaptosomes 479 Solvent Synthesis effects 27,51 of 1,4-benzenediamine 344 on drug conformation 168 binding parameters in bioactive .... 320 macroscopic 168 bioactive 319-339 microscopic 168 computer-assisted 321 hyperdiscriminative 56 of Depoprovera proposed by com­ hypodiscriminative 56 puter program 345/ interactions, solute43 of drugs by a computer program 341-352 molecular changes in 44 of P G F « 346 isodiscriminative 56 proposed by computer program .. 347/ solubility of water in apolar 55i reaction parameters in bioactive .... 320 systems 54 software development for Statistical mechanics 9 organic 341-352 Statistical methods in Q S A R 66 transport parameters in bioactive .... 320 Steric effects 25,35,39,48,59 Synthetic analysis, computerassisted 527-549 on biological activity, influence of 45 Systematic conformational search 209 substituent constants for 23 hindrance 45 of motions 48 Τ repulsion 48, 49 105 substituent constant ( s ) 25,35,45 Taft polar substituent constant STERIMOL 37 T B G ( see Thyroxine-binding globulin ) parameters 50 Strain energy 84, 87,108 T B P A ( see Thyrozine-binding prealbumen ) torsional 85 553 Structural models 320 T D Tetracycline antibiotics, structureStructure-activity relationships activity relationships of 142 (SAR) 103-125 l,2,3,4-Tetrahydrol,4-epoxynaphthaapplications of pattern recognition 104 lenes 459 molecular basis of 161-183 292 quantitative ( Q S A R ) 21-68 Tetraiodothyroactive structures in sympathomimetic amines 441 2,3,5,6-Tetramethyldinitrosopiperazine 571 of tetracycline antibiotics 142 2,3,5,6-Tetramethyl di-N-nitrosoStructure-activity studies 107/ piperazine 562 of enzymes 194 243 Substituent effects 61 Thebaines, oripavines/ 82 Substrate(s) 191 Thermal bond length shortening 82 -active site complex 175 Thermal vibration in crystals 302,306 binding 165, 320 Thiocholine 325,326/ computer-aided design of 194 Thiolcarbamate herbicides Thiolcarbamate, isolipophilic 332 -enzyme interactions, electronic mechanisms in 175 Thyroactive acid structures 295 interactions compounds, hydrogen bonding of .. 286 enzyme10 crystal structures 287/ modeling receptor and 189-201 structures, hydrogen bond direc­ Substructures 106 tionality in 288f-289f bay-region 118 K-region 118 Thyroid -binding proteins 294f Subtilisin 199 hormones 281,282/ inhibitor of 199 cisoid/transoid conformation of .. 283 model of active site region of 199 diphenyl ether conformation of .. 286 stereoview of 200/ distal/proximal 3'-substituents of 283 boronate inhibitor to 202/ and metabolites 294f Sympath-1, energy contours for 405/

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2

5 0

In Computer-Assisted Drug Design; Olson, E., el al.; ACS Symposium Series; American Chemical Society: Washington, DC, 1979.

619

Publication Date: November 28, 1979 | doi: 10.1021/bk-1979-0112.ix001

INDEX Thyroid (continued) hormones (continued) protein binding characteristics of 292 -receptor interactions, binding models 281-297 Thyronine nucleus 286 Thyronine structures 295 Thyroxine 281-297, 282/, 284/ -binding globulin ( T B G ) 281,295 binding affinity of 297 -binding prealbumen (TBPA) 281,293,295 binding affinity of 297 -receptor-interaction, model of .... 296/ diphenyl ether conformation of 282/ Topographical similarity 417 Torsion angles 472 Torsional barriers 388 Torsional interactions 386 Torsional strain energy 85 Toxicity 586 cardenolide 259 Transform 543 Transition state analogues 149-158 of alternative 154 calculation 152 structure, determination of 149 Treloxinate 373 chemical structures of 376/-377/ Triiodothyronine 281-297, 282/ Trypsin bound to the trypsin inhibitor complex, stereoview of the active site region of 196/ inhibitor complex, stereoview of the active site region of trypsin bound to the 196/ inhibitor, pancreatic ( P T I ) 194 substrates 194 -trypsin inhibitor complex 191 + trypsin inhibitor, stereoview of . 198/ Tryptamine(s) 163,177 congeners, reactive sites in 177 derivatives 163,169 Tumors of the esophagus 554

U Uncoupling activity Ureas, herbicidal Urea herbicides

521 516*,523f 332/ 331

V Valence energy 304 Valyl amino acid residues 407 Valyl residue 410/ contour map for 411/ energy contours for 409/ van der Waals' interactions 192 Variable retention of diatomic differ­ ential overlap ( V R D D O ) approximation 418 Variance feature selection in A D A P T 116 Vibration in crystals, thermal 82 V R D D O (Variable retention of di­ atomic differential overlap) approximation 418

W Water in apolar solvents, solubility of desolvation of /hexane partition coefficient /octanol partition coefficient Wave functions, C N D O / 2 Wave functions, I N D O

55i 54 553 553 427 427

X X-ray crystallographic analysis to the de­ sign of conformationally de­ fined analogs of methamphetamine, application of C N D O / 2 calculations and 439-481 crystallography 443 diffraction 79 studies of phenylethylamines 467

Ζ Zipper hypothesis

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